{"id":1288,"date":"2022-06-03T19:32:05","date_gmt":"2022-06-03T10:32:05","guid":{"rendered":"http:\/\/localhost:8000\/kobalab\/?page_id=1288"},"modified":"2026-04-01T15:30:33","modified_gmt":"2026-04-01T06:30:33","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n
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2025<\/a><\/div>\n\n\n\n
2024<\/a><\/div>\n\n\n\n
2023<\/a><\/div>\n\n\n\n
2022<\/a><\/div>\n\n\n\n
2021<\/a><\/div>\n\n\n\n
2020<\/a><\/div>\n\n\n\n
2019<\/a><\/div>\n\n\n\n
2018<\/a><\/div>\n\n\n\n
2017<\/a><\/div>\n<\/div>\n\n\n\n

2025<\/h2>\n\n\n\n

<\/i> Journal<\/strong><\/strong><\/h3>\n\n\n\n
  1. Eri Kuroda and Ichiro Kobayashi. “Predictive Inference Models for Real-world Physical Environments”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Fuji publisher, 2025, in press.<\/li>
  2. Ying LUO and Ichiro Kobayashi, BrainLM: Enhancing Brain Encoding and Decoding Capabilities with Applications in Multilingual Learning,Journal of Advanced Computational Intelligence and Intelligent Informatics, Fuji publisher, 2025, in press.<\/li><\/ol>\n\n\n\n

    <\/i> International Conference<\/strong><\/h3>\n\n\n\n
    1. Mizuki Arai, Tatsuya Ishigaki, Masayuki Kawarada, Hiroya Takamura, Ichiro Kobayashi. “Evaluating\u00a0LLMs\u2019 Ability to Understand Numerical Time Series for Text Generation”, INLG2025, Hanoi, Vietnam, Nov. 2025.<\/li>
    2. Eri Kuroda and Ichiro Kobayashi. “Verbal Representation of Object Collision Prediction Based on Physical CommonSense Knowledge”, 2025 17th International Conference on Machine Learning and Computing (ICMLC2025), Guangzhou, China, Feb. 2025.<\/li>
    3. Anna Sato and Ichiro Kobayashi. \u201cDecoding Semantic Representations in the Brain Under Language Stimuli with Large Language Models\u201d, Workshop of Writing Aids at the Crossroads of AI, Cognitive Science and NLP WR-AI-CogS, COLING2025, Abu Dhabi, UAE, Jan. 2025.<\/li><\/ol>\n\n\n\n

      <\/i> Domestic Conference (in Japanese)<\/strong><\/h3>\n\n\n\n
      1. \u77f3\ufa11\u6587\u90fd\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u8996\u899a\u4f53\u9a13\u306b\u95a2\u3059\u308b\u8133\u5185\u8868\u8c61\u306e\u518d\u69cb\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      2. \u5ddd\u9089\u3082\u3086\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u611f\u60c5\u3068\u97f3\u697d\u5c5e\u6027\u306b\u7740\u76ee\u3057\u305f\u97f3\u697d\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      3. \u6749\u6751\u771f\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u56e0\u679c\u30b0\u30e9\u30d5\u306b\u57fa\u3065\u304f\u5831\u916c\u63a8\u5b9a\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u30aa\u30d5\u30dd\u30ea\u30b7\u30fc\u8a55\u4fa1\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      4. \u5468 \u6615\u6021\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cAn Attempt to apply Natural Language Processing Technology into Traditional Literature Research\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      5. \u4e45\u4fdd\u5c71\u77b3\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u30b3\u30de\u30f3\u30c9\u306e\u8a00\u8a9e\u5316\u306b\u3088\u308b\u81ea\u7136\u8a00\u8a9e\u306b\u57fa\u3065\u304f\u30ed\u30dc\u30c3\u30c8\u64cd\u4f5c\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      6. \u676d \u96e8\u6b23\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u52d5\u753b\u751f\u6210\u306b\u304a\u3051\u308b\u5236\u5fa1\u624b\u6cd5\u306e\u958b\u767a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      7. \u912d \u30a8\u30a4\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u904e\u7a0b\u3092\u7528\u3044\u305f\u30c6\u30ad\u30b9\u30c8\u304b\u3089\u306e\u6709\u5bb3\u8868\u73fe\u9664\u53bb\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c87\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u7acb\u547d\u9928\u5927\u5b66\uff0c\u5927\u962a\uff0c2025\u5e743\u6708\uff0e<\/li>
      8. \u65b0\u4e95\u6df1\u6708\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u30d7\u30ed\u30f3\u30d7\u30c8\u306e\u8a00\u8a9e\u306b\u3088\u308b\u6570\u5024\u6642\u7cfb\u5217\u89e3\u91c8\u80fd\u529b\u306e\u5909\u5316\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      9. \u5c0f\u570b\u601c\u7f8e\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u751f\u6210\u30c7\u30fc\u30bf\u306b\u57fa\u3065\u3044\u305f\u65e5\u672c\u8a9e\u306e\u6642\u9593\u95a2\u4fc2\u63a8\u5b9a\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      10. \u4f0a\u6771\u6075\u7f8e\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u5b9a\u91cf\u7684\u63a8\u8ad6\u6a5f\u80fd\u306e\u5b9f\u73fe\u306b\u5411\u3051\u3066\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      11. \u53e4 \u6cf3\u6b23\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cBERT\u306b\u57fa\u3065\u3044\u305fRussell\u5186\u74b0\u30e2\u30c7\u30eb\u306e\u611f\u60c5\u5206\u6790\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      12. \u4f50\u85e4\u674f\u5948\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u8133\u5185\u610f\u5473\u8868\u8c61\u89e3\u8aad\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      13. \u5e73\u91ce\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u534a\u81ea\u5df1\u56de\u5e30\u7684\u306b\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u6d3b\u7528\u3059\u308b\u30c8\u30ec\u30fc\u30b9\u30d9\u30fc\u30b9\u306e\u610f\u56f3\u53cd\u6620\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      14. \u4e2d\u91ce\u7531\u52a0\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4e8c\u3064\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u95a2\u4fc2\u3092\u8a18\u8ff0\u3059\u308b\u81ea\u7136\u8a00\u8a9e\u6587\u751f\u6210\u624b\u6cd5\u306e\u5b9f\u6e2c\u30c7\u30fc\u30bf\u9069\u7528\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      15. \u5f35 \u8fb0\u8056\u5b50\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5c24\u5ea6\u6700\u5927\u5316\u306b\u57fa\u3065\u304f\u81ea\u7136\u8a00\u8a9e\u306b\u3088\u308b\u591a\u6bb5\u63a8\u8ad6\u904e\u7a0b\u306e\u62bd\u51fa\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      16. Wang Yuanyi\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cMCMC\u3092\u7528\u3044\u305f\u524d\u63d0\u691c\u7d22\u306b\u3088\u308bLLM\u306e\u4eee\u8aac\u63a8\u8ad6\u80fd\u529b\u306e\u5f37\u5316\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a(NLP2025)\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      17. Muxuan Liu\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cJaSocial\uff1aLLM \u306e\u793e\u4f1a\u7684\u77e5\u80fd\u3092\u8a55\u4fa1\u3059\u308b\u305f\u3081\u306e\u65e5\u672c\u8a9e\u656c\u8a9e\u4f7f\u7528\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      18. Muxuan Liu\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797 \u4e00\u90ce\uff0e\u300c\u300c\u5fc3\u306e\u4e2d\u306e\u8a00\u8449\u300d\u306f\u3069\u306e\u3088\u3046\u306b\u4e88\u6e2c\u3067\u304d\u308b\u304b\uff1f \u2015\u8907\u6570\u306e\u30e2\u30c0\u30ea\u30c6\u30a3\u306e\u7279\u5fb4\u306b\u57fa\u3065\u304f\u8133\u6d3b\u52d5\u30c7\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u30d7\u30ed\u30bb\u30b9\u306e\u69cb\u7bc9\u2015\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li>
      19. Luo Ying\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cBrainLM\u3092\u7528\u3044\u305f\u591a\u8a00\u8a9e\u5b66\u7fd2\u3067\u306e\u8ee2\u79fb\u5b66\u7fd2\u6027\u80fd\u306e\u691c\u8a3c\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u51fa\u5cf6\u30e1\u30c3\u30bb\u9577\u5d0e\uff0c\u9577\u5d0e\uff0c2025\u5e743\u6708\uff0e<\/li><\/ol>\n\n\n\n
        \n\n\n\n

        2024<\/h2>\n\n\n\n

        <\/i> Journal<\/strong><\/h3>\n\n\n\n

        <\/i> International Conference<\/strong><\/h3>\n\n\n\n
        1. Ying Luo, Satoshi Nishida and Ichiro Kobayashi. “Sex Differences in Brain Information Processing: Insights from Specific Brain Regions and Hemispheric Connectivity”, The International Workshop on Mesoscopic Brain-wide Connectivity Atlas (MBCA 2024), Bangkok, Thailand, Dec. 2024.<\/li>
        2. Muxuan Liu, Tatsuya Ishigaki, Yusuke Miyao, Hiroya Takamura and Ichiro Kobayashi. \u201cEvaluating LlaMA-2’s Adaptation to Social Context in Japanese Emails via Fine-Tuning\u201c. The 38th Pacific Asia Conference on Language, Information, and Computation (PACLIC 38), Tokyo, Japan, Dec. 2024.<\/li>
        3. Fumi Ishizaki and Ichiro Kobayashi. “A Study on Brain Decoding of Image Stimuli Using a Diffusion Model”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        4. Megumi Ito and Ichiro Kobayashi. “Toward Fuzzy Reasoning with Large Language Models”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        5. Mana Ueno and Ichiro Kobayashi. “A Study of Gender Bias in the Effects of Context Using BERT”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        6. Moyu Kawabe and Ichiro Kobayashi. “A Study of Emotion-based Music Generation using Diffusion Model”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        7. Mariko Sugimura and Ichiro Kobayashi. “The Effect of Different Experimental Settings on Off-Policy Evaluations”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        8. Yukako Nakano and Ichiro Kobayashi. “Generation of Natural Language Responses to Questions about the Relationship between Two Time-series Data”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        9. Ying Luo and Ichiro Kobayashi. “Exploring Individual and Sex Differences from Brain EEG Signals under Music Stimuli”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        10. Eri Kuroda, Yuki Taya and Ichiro Kobayashi. “Verbal Description Focusing on Physical Properties of Real-World Environments”, 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2024), Hyogo, Japan, Nov. 2024. <\/i><\/a><\/li>
        11. Muxuan Liu and Ichiro Kobayashi. “Do Feature Representations from Different Language Models Affect Accuracy of Brain Encoding Models’ Predictions?”, The 2024 IEEE Conference on Systems, Man, and Cybernetics (IEEE-SMC2024), Sarawak, Malaysia, Oct. 2024. <\/i><\/li>
        12. Yuka Yokogawa, Tatsuya Ishigaki, Yusuke Miyao, Hiroya Takamura and Ichiro Kobayashi. “Leveraging Plug-and-Play Models for Rhetorical Structure Control in Text Generation”, The 17th International Natural Language Generation Conference (INLG2024), Tokyo, Japan, Sep. 2024. <\/i><\/a><\/li>
        13. Tomoe Taniguchi, Daichi Mochihashi, Ichiro Kobayashi. “Learning Adverbs with Spectral Mixture Kernels”, The 62nd Annual Meeting of the Association for Computational Linguistics (ACL2024), Bangkok, Thailand, Aug. 2024. <\/i><\/a><\/li><\/ol>\n\n\n\n

          Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
          1. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Professionalism-Aware Pre-Finetuning for Profitability Ranking”, 33rd ACM International Conference on Information and Knowledge Management (CIKM2024), Idaho, USA, Oct. 2024. <\/i><\/a><\/li>
          2. Wenjie Zhong, Jason Naradowsky, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao, “Who Said What: Formalization and Benchmarks for the Task of Quote Attribution”, The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), Torino, Italy, May. 2024. <\/i><\/a><\/li>
          3. Erica K. Shimomoto, Edison Marrese-Taylor, Ichiro Kobayashi, Hiroya Takamura, Yusuke Miyao. “Introducing Spatial Information and a Novel Evaluation Scheme for Open-Domain Live Commentary Generation”, The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP2024), Findings, Florida, USA, Nov. 2024. <\/i><\/a><\/li>
          4. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “The Impact of Language on Arithmetic Proficiency: A Multilingual Investigation with Cross-Agent Checking Computation”, 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL2024), Short Paper, Mexico, June. 2024. <\/i><\/a><\/li><\/ol>\n\n\n\n

            <\/i> Preprint<\/strong><\/h3>\n\n\n\n

            Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
            1. Felix Giovanni Virgo, Fei Cheng, Lis Kanashiro Pereira, Masayuki Asahara\"\", Ichiro Kobayashi, Sadao Kurohashi, “AcTED: Automatic Acquisition of Typical Event Duration for Semi-supervised Temporal Commonsense QA”, arXiv, 2024. <\/i><\/a><\/li>
            2. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “FinGen: A Dataset for Argument Generation in Finance”, arXiv, 2024. <\/i><\/a><\/li>
            3. Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Enhancing Investment Opinion Ranking through Argument-Based Sentiment Analysis”, arXiv, 2024. <\/i><\/a><\/li>
            4. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Enhancing Financial Sentiment Analysis with Expert-Designed Hint”, arXiv, 2024. <\/i><\/a><\/li>
            5. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Hierarchical Organization Simulacra in the Investment Sector”, arXiv, 2024. <\/i><\/a><\/li>
            6. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “GADFA: Generator-Assisted Decision-Focused Approach for Opinion Expressing Timing Identification”, arXiv, 2024. <\/i><\/a><\/li>
            7. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Distilling Analysis from Generative Models for Investment Decisions”, arXiv, 2024. <\/i><\/a><\/li><\/ol>\n\n\n\n

              <\/i> Domestic Conference (in Japanese)<\/p>\n\n\n\n

              1. \u65b0\u4e95\u6df1\u6708\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u306e\u6570\u5024\u6642\u7cfb\u5217\u89e3\u91c8\u80fd\u529b\u306e\u691c\u8a3c\u300d\uff0e\u7b2c262\u56de \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u767a\u8868\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2024\u5e7412\u6708\uff0e<\/li>
              2. \u4f0a\u6771\u6075\u7f8e\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u30d5\u30a1\u30b8\u30a3\u63a8\u8ad6\u306e\u5b9f\u73fe\u3078\u5411\u3051\u3066\u300d\uff0e\u7b2c40\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff08FSS2024\uff09\uff0c\u6919\u5c71\u5973\u5b66\u5712\u5927\u5b66\uff0c\u611b\u77e5\uff0c2024\u5e749\u6708\uff0e<\/li>
              3. \u4f50\u85e4\u674f\u5948\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u8133\u5185\u610f\u5473\u8868\u8c61\u89e3\u8aad\u300d\uff0e\u7b2c40\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff08FSS2024\uff09\uff0c\u6919\u5c71\u5973\u5b66\u5712\u5927\u5b66\uff0c\u611b\u77e5\uff0c2024\u5e749\u6708\uff0e<\/li>
              4. \u4e09\u6d66 \u8863\u91cc\uff0c\u5c0f\u6797 \u4e00\u90ce\uff0e\u300c\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u30d2\u30c8\u8133\u5185\u3067\u306e\u611f\u60c5\u53cd\u5fdc\u90e8\u4f4d\u7279\u5b9a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u7b2c40\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff08FSS2024\uff09\uff0c\u6919\u5c71\u5973\u5b66\u5712\u5927\u5b66\uff0c\u611b\u77e5\uff0c2024\u5e749\u6708\uff0e<\/li>
              5. \u9ed2\u7530\u5f57\u8389\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u7269\u7406\u7684\u5e38\u8b58\u3092\u3075\u307e\u3048\u305f\u7269\u4f53\u885d\u7a81\u6642\u306e\u4e88\u6e2c\u306b\u304a\u3051\u308b\u8a00\u8a9e\u8868\u73fe\u300d\uff0e\u7b2c40\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff08FSS2024\uff09\uff0c\u6919\u5c71\u5973\u5b66\u5712\u5927\u5b66\uff0c\u611b\u77e5\uff0c2024\u5e749\u6708\uff0e<\/li>
              6. \u77f3\ufa11\u6587\u90fd\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u753b\u50cf\u523a\u6fc0\u4e0b\u306e\u8133\u5185\u60c5\u5831\u89e3\u8aad\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              7. \u4f0a\u6771\u6075\u7f8e\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8a00\u8a9e\u306b\u3088\u308b\u5b9a\u91cf\u7684\u63a8\u8ad6\u306e\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u3078\u306e\u5c0e\u5165\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              8. \u4e0a\u91ce\u8309\u5948\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cBERT\u306e\u6ce8\u610f\u6a5f\u69cb\u306b\u7740\u76ee\u3057\u305f\u30b8\u30a7\u30f3\u30c0\u30fc\u30d0\u30a4\u30a2\u30b9\u306e\u4e00\u8003\u5bdf\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              9. \u5ddd\u9089\u3082\u3086\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u611f\u60c5\u306b\u57fa\u3065\u3044\u305f\u97f3\u697d\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              10. \u6749\u6751\u771f\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u53cd\u5b9f\u4eee\u60f3\u6a5f\u68b0\u5b66\u7fd2\u306b\u304a\u3051\u308b\u30aa\u30d5\u30dd\u30ea\u30b7\u30fc\u8a55\u4fa1\u306e\u4e00\u8003\u5bdf\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              11. \u4e45\u4fdd\u5c71\u77b3\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5236\u5fa1\u30b3\u30de\u30f3\u30c9\u306e\u8a00\u8a9e\u5316\u306b\u3088\u308b\u8a00\u8a9e\u6307\u793a\u64cd\u4f5c\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              12. \u5f35 \u8fb0\u8056\u5b50\uff0c\u6301\u6a4b \u5927\u5730\uff0c\u5c0f\u6797 \u4e00\u90ce\uff0e\u300c\u81ea\u7136\u8a00\u8a9e\u306b\u3088\u308b\u5e30\u7d0d\u7684\u63a8\u8ad6\u904e\u7a0b\u306e\u62bd\u51fa\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              13. \u4e2d\u91ce\u7531\u52a0\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4e8c\u3064\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u6319\u52d5\u6bd4\u8f03\u306b\u57fa\u3065\u304f\u8a18\u8ff0\u6587\u751f\u6210\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              14. \u5e73\u91ce\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u904e\u7a0b\u306b\u57fa\u3065\u304f\u30e2\u30c7\u30eb\u306b\u3088\u308b\u30c8\u30ec\u30fc\u30b9\u304b\u3089\u30e6\u30fc\u30b6\u306e\u610f\u56f3\u3092\u53cd\u6620\u3057\u305f\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              15. \u4e09\u6d66\u8863\u91cc\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u30d2\u30c8\u8133\u5185\u306b\u304a\u3051\u308b\u611f\u60c5\u89e3\u6790\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              16. \u9ed2\u7530\u5f57\u8389\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5b9f\u4e16\u754c\u74b0\u5883\u306e\u7269\u7406\u7279\u6027\u306b\u7740\u76ee\u3057\u305f\u8a00\u8a9e\u8a18\u8ff0\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              17. Luo Ying\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u591a\u8a00\u8a9e\u5b66\u7fd2\u306e\u305f\u3081\u306eBrainLM\u30de\u30eb\u30c1\u30e2\u30fc\u30c0\u30eb\u30e2\u30c7\u30eb\u306b\u3088\u308b\u30a2\u30f3\u30b5\u30f3\u30d6\u30eb\u8ee2\u79fb\u5b66\u7fd2\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c38\u56de\uff09\uff0c\u30a2\u30af\u30c8\u30b7\u30c6\u30a3\u6d5c\u677e\uff0c\u9759\u5ca1\uff0c2024\u5e745\u6708\uff0e<\/i><\/a><\/li>
              18. \u65bd \u4f73\u5764\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8457\u8005\u8b58\u5225\u306b\u57fa\u3065\u304f\u6587\u4f53\u30b9\u30bf\u30a4\u30eb\u5909\u63db\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c86\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u795e\u5948\u5ddd\u5927\u5b66\uff0c\u795e\u5948\u5ddd\uff0c2024\u5e743\u6708\uff0e<\/li>
              19. \u4f0a\u6771\u6075\u7f8e\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u3078\u306e\u5b9a\u91cf\u7684\u63a8\u8ad6\u6a5f\u80fd\u306e\u7d44\u307f\u8fbc\u307f\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              20. \u4f50\u85e4\u674f\u5948\uff0c\u8fd1\u6dfb\u6df3\u4e00\uff0c\u8239\u4e95\u6b63\u592a\u90ce\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u77ed\u6b4c\u56fa\u6709\u306e\u5c5e\u6027\u306b\u5bfe\u5fdc\u3059\u308b\u8133\u5185\u60c5\u5831\u8868\u73fe\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              21. \u4e2d\u91ce\u7531\u52a0\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4e8c\u3064\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u5bfe\u8c61\u3068\u3057\u305f\u7279\u5b9a\u7740\u76ee\u70b9\u306e\u52d5\u5411\u306b\u3064\u3044\u3066\u306e\u8a18\u8ff0\u6587\u751f\u6210\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              22. \u5e73\u91ce\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u904e\u7a0b\u3092\u7528\u3044\u305f\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u306b\u304a\u3051\u308b\u5206\u985e\u5668\u5c0e\u5165\u306e\u7cbe\u5ea6\u3078\u306e\u5f71\u97ff\u306e\u691c\u8a3c\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              23. \u6210\u7530\u767e\u82b1\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6728\u69cb\u9020\u81ea\u5df1\u6ce8\u610f\u6a5f\u69cb\u3092\u7528\u3044\u305f\u6559\u5e2b\u306a\u3057\u7d71\u8a9e\u69cb\u9020\u89e3\u6790\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              24. \u8239\u66f3\u65e5\u4f73\u91cc\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u6d45\u539f\u6b63\u5e78\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6f5c\u5728\u7684\u6b63\u898f\u5206\u5e03\u306b\u3088\u308b\u30a4\u30d9\u30f3\u30c8\u306e\u6642\u9593\u95a2\u4fc2\u306e\u63a8\u5b9a\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              25. \u6a2a\u5ddd\u60a0\u9999\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4fee\u8f9e\u69cb\u9020\u306b\u57fa\u3065\u304d\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u5236\u5fa1\u3059\u308b\u30c6\u30ad\u30b9\u30c8\u751f\u6210\u624b\u6cd5\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li>
              26. Muxuan Liu\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u793e\u4f1a\u7684\u72b6\u6cc1\u3092\u8e0f\u307e\u3048\u305f\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u306b\u3088\u308b\u65e5\u672c\u8a9e\u30e1\u30fc\u30eb\u751f\u6210\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u795e\u6238\u56fd\u969b\u4f1a\u8b70\u5834\uff0c\u5175\u5eab\uff0c2024\u5e743\u6708\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                \n\n\n\n

                2023<\/h2>\n\n\n\n

                <\/i> Journal<\/h3>\n\n\n\n
                1. <\/i> Yuri Murayama and Ichiro Kobayashi. “Towards Question Answering with Multi-hop Reasoning and Calculation over Knowledge using a Neural Network Model with External Memories”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Fuji publisher, Vol. 27, No. 3, pp. 481\u2013489, 2023. <\/i><\/a><\/li><\/ol>\n\n\n\n

                  <\/i> International Conference<\/h3>\n\n\n\n
                  1. <\/i> Yukako Nakano and Ichiro Kobayashi. “Generating a Natural Language Sentence explaining Trends of Two Time-Series Data”, The 24th International Symposium on Advanced Intelligent Systems(ISIS2023), Gwangju, Korea, Dec. 2023. Best Paper Award<\/a>.<\/li>
                  2. <\/i> Satoko Hirano and Ichiro Kobayashi. “Validation of the accuracy of different denoising networks for caption generation using diffusion processes”, The 24th International Symposium on Advanced Intelligent Systems(ISIS2023), Gwangju, Korea, Dec. 2023. Best Presentation Award<\/mark>.<\/li>
                  3. Haruka Iwai and Ichiro Kobayashi. “A Study on a Developmental Artificial Neural Networks that enables the Transfer of Multiple Functions”, The 24th International Symposium on Advanced Intelligent Systems(ISIS2023), Gwangju, Korea, Dec. 2023.<\/li>
                  4. <\/i> Haruka Kawasaki, Satoshi Nishida and Ichiro Kobayashi. “Localization and Representation of Visual and Language Information in the Human Brain”, The 24th International Symposium on Advanced Intelligent Systems(ISIS2023), Gwangju, Korea, Dec. 2023. Best Presentation Award.<\/mark><\/li>
                  5. <\/i> Momoka Narita, Daichi Mochihashi and Ichiro Kobayashi. “Parsing with Tree Structure Self-attention Mechanism”, The 24th International Symposium on Advanced Intelligent Systems(ISIS2023), Gwangju, Korea, Dec. 2023. Best Presentation Award.<\/mark><\/li>
                  6. Muxuan Liu, Tatsuya Ishigaki, Yusuke Miyao, Hiroya Takamura and Ichiro Kobayashi. “Constructing a Japanese Business Email Corpus Based on Social Situations”, Pacific Asia Conference on Language, Information and Computation(PACLIC37), Hong Kong, Dec. 2023.<\/li>
                  7. Haruka Iwai and Ichiro Kobayashi. “A Study on Developmental Artificial Neural Networks that Integrate Multiple Functions using Variational Autoencoder”, 2023 10th International Conference on Soft Computing & Machine Intelligence(ISCMI2023), Mexico city, Mexico, Nov. 2023.<\/li>
                  8. Eri Kuroda and Ichiro Kobayashi. “Predictive Inference Model of the Physical Environment that emulates Predictive Coding”, 26th International Conference on Discovery Science(DS2023), Porto, Portugal, Oct. 2023. <\/i><\/a><\/li>
                  9. Haruka Kawasaki, Satoshi Nishida and Ichiro Kobayashi. “Exploring Hierarchical Changes in Functional Brain Network Hubs through Brain-activity Prediction with Convolutional Neural Networks”, The 2023 IEEE Conference on Systems, Man, and Cybernetics(IEEE-SMC2023), Oahu, Hawaii, Oct. 2023.<\/li>
                  10. Ying Luo and Ichiro Kobayashi. “BrainLM: Estimation of Brain Activity evoked Linguistic Stimuli utilizing Large Language”, The 2023 IEEE Conference on Systems, Man, and Cybernetics(IEEE-SMC2023), Oahu, Hawaii, Oct. 2023. Selected as one of seven finalists for Best Paper and Best Student Paper Award<\/mark>.<\/mark><\/li>
                  11. Anna Sato, Junichi Chikazoe, Shotaro Funai, Daichi Mochihashi, Yutaka Shikano, Masayuki Asahara, Satoshi Iso and Ichiro Kobayashi. “Investigation of Information Processing Mechanisms in the Human Brain during Reading Tanka Poetry”, 32nd International Conference on Artificial Neural Networks(ICANN2023), Crete, Greece, Sep. 2023.<\/li>
                  12. Muxuan Liu and Ichiro Kobayashi. “\u65e5\u672c\u8a9e\u6559\u80b2\u306b\u304a\u3051\u308bAI\u6559\u80b2\u652f\u63f4\u30b7\u30b9\u30c6\u30e0\u306e\u904e\u53bb\u3068\u672a\u6765”, JSAA-ICNTJ2023 (\u8c6a\u5dde\u65e5\u672c\u7814\u7a76\u5b66\u4f1a\u7814\u7a76\u5927\u4f1a \/ \u56fd\u969b\u7e4b\u751f\u8a9e\u5927\u4f1a), Sydney, Australia, Sep. 2023.<\/li>
                  13. Eri Kuroda and Ichiro Kobayashi. “Extraction of Motion Change Points based on the Physical Characteristics of Objects”, 2023 IEEE the 4th International Conference on Pattern Recognition and Machine Learning (PRML2023), Xinjiang, China, Aug. 2023.<\/li><\/ol>\n\n\n\n

                    Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                    1. Erica Kido Shimomoto, Edison Marrese-Taylor, Hiroya Takamura, Ichiro Kobayashi, Hideki Nakayama, Yusuke Miyao. “Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video Grounding”, The 61st Annual Meeting of the Association for Computational Linguistics (ACL2023), Findings, Toronto, Canada, July. 2023. <\/i><\/a><\/li>
                    2. Chung-Chi Chen, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Improving Numeracy by Input Reframing and Quantitative Pre-Finetuning Task”, The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL2023), Findings, Dubrovnik, Croatia, May. 2023. <\/i><\/a><\/li>
                    3. Wenjie Zhong, Jason Naradowsky, Hiroya Takamura, Ichiro Kobayashi, Yusuke Miyao. “Fiction-Writing Mode: An Effective Control for Human-Machine Collaborative Writing”, The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL2023), Dubrovnik, Croatia, May. 2023. <\/i><\/a><\/li><\/ol>\n\n\n\n

                      <\/i> Preprint<\/strong><\/h3>\n\n\n\n

                      Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                      1. Fei Cheng, Masayuki Asahara, Ichiro Kobayashi, Sadao Kurohashi. “Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning”, arXiv, 2023. <\/i><\/a><\/li><\/ol>\n\n\n\n

                        <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                        1. \u5ca9\u4e95 \u9065\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5909\u5206\u81ea\u5df1\u7b26\u53f7\u5316\u5668\u3092\u7528\u3044\u305f\u6a5f\u80fd\u3092\u878d\u5408\u3059\u308b \u767a\u9054\u578b\u4eba\u5de5\u795e\u7d4c\u56de\u8def\u7db2\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0c\u7b2c39\u56de \u30d5\u30a1\u30b8\u30a3 \u30b7\u30b9\u30c6\u30e0 \u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff08FSS2023\uff09\uff0c\u30f4\u30a3\u30e9\u30fb\u30c7\u30fb\u30de\u30ea\u30a2\u30fc\u30b8\u30e5\u8efd\u4e95\u6fa4\uff0c\u9577\u91ce\uff0c2023\u5e749\u6708\uff0eFuzzy Special Session Presentation Award<\/a>. <\/i><\/a><\/li>
                        2. \u5ddd\ufa11 \u6625\u4f73\uff0c\u897f\u7530 \u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u30d2\u30c8\u8133\u5185\u306b\u304a\u3051\u308b\u8996\u899a\u30fb\u610f\u5473\u60c5\u5831\u306e\u5c40\u5728\u3068\u8868\u73fe\u306e\u8abf\u67fb\u300d\uff0c\u7b2c39\u56de \u30d5\u30a1\u30b8\u30a3 \u30b7\u30b9\u30c6\u30e0 \u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff08FSS2023\uff09\uff0c\u30f4\u30a3\u30e9\u30fb\u30c7\u30fb\u30de\u30ea\u30a2\u30fc\u30b8\u30e5\u8efd\u4e95\u6fa4\uff0c\u9577\u91ce\uff0c2023\u5e749\u6708\uff0e<\/i><\/a><\/li>
                        3. Anna Sato, Junichi Chikazoe, Shotaro Funai, Daichi Mochihashi, Yutaka Shikano, Masayuki Asahara, Satoshi Iso and Ichiro Kobayashi. \u300c\u77ed\u6b4c\u3092\u8aad\u3093\u3060\u6642\u306e\u611f\u60c5\u306b\u95a2\u3059\u308b\u8133\u6d3b\u52d5\u89e3\u6790\u300d\uff0e\u7b2c46\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a\uff0c\u4ed9\u53f0\u56fd\u969b\u30bb\u30f3\u30bf\u30fc\uff0c\u5bae\u57ce\uff0c2023\u5e748\u6708\uff0e<\/li>
                        4. \u4f50\u85e4\u674f\u5948\uff0c\u8fd1\u6dfb\u6df3\u4e00\uff0c\u8239\u4e95\u6b63\u592a\u90ce\uff0e\u6301\u6a4b\u5927\u5730\uff0e\u9e7f\u91ce\u8c4a\uff0e\u6d45\u539f\u6b63\u5e78\uff0e\u78ef\u6681\uff0e\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u77ed\u6b4c\u3092\u8aad\u3080\u969b\u306e\u60c5\u52d5\u306b\u95a2\u3059\u308b\u30d2\u30c8\u8133\u5185\u306e\u60c5\u5831\u51e6\u7406\u6a5f\u69cb\u306e\u89e3\u6790\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        5. \u5f35 \u8fb0\u8056\u5b50\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u7406\u7531\u3092\u8868\u3059\u624b\u304c\u304b\u308a\u8868\u73fe\u306b\u57fa\u3065\u304f\u975e\u8ad6\u7406\u7684\u306a\u8a00\u8a9e\u63a8\u8ad6\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        6. \u4e2d\u91ce\u7531\u52a0\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4e8c\u3064\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u52d5\u5411\u3092\u8a18\u8ff0\u3059\u308b\u81ea\u7136\u8a00\u8a9e\u6587\u751f\u6210\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        7. \u5e73\u91ce\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u904e\u7a0b\u3092\u7528\u3044\u305f\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u6027\u80fd\u5411\u4e0a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        8. \u5ca9\u4e95\u9065\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6587\u6cd5\u5909\u5206\u81ea\u5df1\u7b26\u53f7\u5316\u5668\u3092\u7528\u3044\u305f\u6a5f\u80fd\u3092\u878d\u5408\u3059\u308b\u767a\u9054\u578b\u4eba\u5de5\u795e\u7d4c\u56de\u8def\u7db2\u958b\u767a\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        9. \u5ddd\ufa11\u6625\u4f73\uff0c\u8302\u6728\u6bd4\u5948\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u97f3\u697d\u523a\u6fc0\u4e0b\u306e\u30d2\u30c8\u8133\u5185\u306b\u304a\u3051\u308b\u6027\u5dee\u306e\u8abf\u67fb\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        10. \u6210\u7530\u767e\u82b1\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6728\u69cb\u9020\u81ea\u5df1\u6ce8\u610f\u6a5f\u69cb\u306b\u3088\u308a\u6f5c\u5728\u7684\u69cb\u6587\u6728\u3092\u8868\u73fe\u3059\u308b\u6559\u5e2b\u3042\u308a\u7d71\u8a9e\u69cb\u9020\u89e3\u6790\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        11. \u8239\u66f3\u65e5\u4f73\u91cc\uff0c\u6728\u6751\u9ebb\u53cb\u5b50\uff0cLis Kanashiro Pereira\uff0c\u6d45\u539f\u6b63\u5e78\uff0cFei Cheng\uff0c\u8d8a\u667a\u7dbe\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u5b66\u7fd2\u3092\u7528\u3044\u305f\u6642\u9593\u3092\u8a8d\u8b58\u3059\u308b\u6c4e\u7528\u8a00\u8a9e\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        12. \u4e09\u6d66\u8863\u91cc\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u30d2\u30c8\u8133\u5185\u306b\u304a\u3051\u308b\u611f\u60c5\u63a8\u5b9a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        13. Muxuan Liu\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u793e\u4f1a\u7684\u72b6\u6cc1\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u542b\u3080\u65e5\u672c\u8a9e\u30b3\u30fc\u30d1\u30b9\u306e\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3078\u306e\u9069\u7528\u6027\u691c\u8a3c\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        14. \u9ed2\u7530\u5f57\u8389\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4e88\u6e2c\u7b26\u53f7\u5316\u3092\u6a21\u3057\u305f\u7269\u7406\u74b0\u5883\u306e\u4e88\u6e2c\u63a8\u8ad6\u30e2\u30c7\u30eb\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        15. \u7f85 \u685c\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300cThe Music LP Dataset: \u53d7\u52d5\u7684\u30fb\u80fd\u52d5\u7684\u97f3\u697d\u523a\u6fc0\u4e0b\u306e\u30d2\u30c8\u8133\u6d3b\u52d5 \u306b\u5bfe\u3059\u308b\u8133\u6ce2\u8a08\u6e2c\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        16. \u7530\u5c4b\u4f91\u5e0c\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u5b9f\u4e16\u754c\u306b\u304a\u3051\u308b\u7269\u7406\u5236\u7d04\u3092\u8e0f\u307e\u3048\u305f\u8a00\u8a9e\u306b\u3088\u308b\u63a8\u8ad6\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        17. \u6751\u5c71\u53cb\u7406\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8868\u30c7\u30fc\u30bf\u306e\u6ce8\u76ee\u3059\u3079\u304d\u7279\u5fb4\u306b\u3064\u3044\u3066\u8ff0\u3079\u308b\u30c6\u30ad\u30b9\u30c8\u306e\u751f\u6210\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        18. \u6ff1\u5712\u4f91\u7f8e\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u30c7\u30fc\u30bf\u304b\u3089\u306e\u8a00\u8a9e\u751f\u6210\u306b\u304a\u3051\u308b\u30b9\u30bf\u30a4\u30eb\u3068\u5185\u5bb9\u306e\u5206\u96e2\u300d\uff0e\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c37\u56de\uff09\uff0c\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff0c\u718a\u672c\uff0c2023\u5e746\u6708\uff0e<\/i><\/a><\/li>
                        19. \u8302\u6728\u6bd4\u5948\uff0c\u5ddd\ufa11\u6625\u4f73\uff0c\u7f85 \u685c\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u97f3\u697d\u523a\u6fc0\u4e0b\u306e\u8133\u5185\u60c5\u5831\u51e6\u7406\u306b\u304a\u3051\u308b\u7537\u5973\u5dee\u306e\u5206\u6790\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c85\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u96fb\u6c17\u901a\u4fe1\u5927\u5b66\uff0c\u6771\u4eac\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        20. \u5ca9\u4e95\u9065\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6a5f\u80fd\u3092\u8ee2\u79fb\u3059\u308b\u767a\u9054\u578b\u4eba\u5de5\u795e\u7d4c\u56de\u8def\u7db2\u958b\u767a\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c85\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u96fb\u6c17\u901a\u4fe1\u5927\u5b66\uff0c\u6771\u4eac\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        21. \u7530\u53e3\u9065\u9999\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6ce8\u610f\u6a5f\u69cb\u3092\u5c0e\u5165\u3057\u305f\u7279\u5fb4\u91cf\u62bd\u51fa\u306b\u57fa\u3065\u304f\u753b\u50cf\u523a\u6fc0\u4e0b\u306e\u8133\u5185\u72b6\u614b\u63a8\u5b9a\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c85\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u96fb\u6c17\u901a\u4fe1\u5927\u5b66\uff0c\u6771\u4eac\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        22. <\/i> \u675c \u9759\u6021\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u753b\u50cf\u8cea\u554f\u5fdc\u7b54\u306b\u57fa\u3065\u304f\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c85\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u96fb\u6c17\u901a\u4fe1\u5927\u5b66\uff0c\u6771\u4eac\uff0c2023\u5e743\u6708\uff0eStudent Encouragement Award of IPSJ National Convention<\/a>\uff0e<\/i><\/a><\/li>
                        23. Yiwen Fang\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u52d5\u753b\u50cf\u5185\u306b\u304a\u3051\u308b\u8907\u6570\u4eba\u306e\u52d5\u4f5c\u8b58\u5225\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c85\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u96fb\u6c17\u901a\u4fe1\u5927\u5b66\uff0c\u6771\u4eac\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        24. \u9ed2\u7530\u5f57\u8389\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u7269\u7406\u74b0\u5883\u306b\u304a\u3051\u308b\u30d2\u30c8\u8133\u5185\u3067\u306e\u4e88\u6e2c\u7b26\u53f7\u5316\u3092\u6a21\u5023\u3057\u305f\u5909\u5316\u70b9\u4e88\u6e2c\u30e2\u30c7\u30eb\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c85\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u96fb\u6c17\u901a\u4fe1\u5927\u5b66\uff0c\u6771\u4eac\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        25. \u4f50\u85e4\u674f\u5948\uff0c\u8fd1\u6dfb\u6df3\u4e00\uff0c\u8239\u4e95\u6b63\u592a\u90ce\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u9e7f\u91ce\u8c4a\uff0c\u6d45\u539f\u6b63\u5e78\uff0c\u78ef \u6681\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u77ed\u6b4c\u3092\u8aad\u3080\u969b\u306e\u60c5\u52d5\u306b\u95a2\u3059\u308b\u8133\u6d3b\u52d5\u306e\u89e3\u6790\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        26. \u5f35\u8fb0\u8056\u5b50\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u624b\u304c\u304b\u308a\u8868\u73fe\u306b\u57fa\u3065\u304f\u975e\u8ad6\u7406\u7684\u306a\u8a00\u8a9e\u63a8\u8ad6\u306e\u5b66\u7fd2\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        27. \u4e2d\u91ce\u7531\u52a0\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4e8c\u3064\u306e\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u95a2\u4fc2\u3092\u8a18\u8ff0\u3059\u308b\u81ea\u7136\u8a00\u8a9e\u6587\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        28. \u5e73\u91ce\u7406\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u62e1\u6563\u904e\u7a0b\u3092\u7528\u3044\u305f\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        29. \u6210\u7530\u767e\u82b1\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6728\u69cb\u9020\u81ea\u5df1\u6ce8\u610f\u6a5f\u69cb\u306b\u3088\u308b\u6559\u5e2b\u3042\u308a\u7d71\u8a9e\u69cb\u9020\u89e3\u6790\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        30. \u8239\u66f3\u65e5\u4f73\u91cc\uff0cLis Kanashiro Pereira\uff0c\u6728\u6751\u9ebb\u53cb\u5b50\uff0c\u6d45\u539f\u6b63\u5e78\uff0cFei Cheng\uff0c\u8d8a\u667a\u7dbe\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u65e5\u672c\u8a9e\u306e\u6642\u9593\u7684\u5e38\u8b58\u3092\u7406\u89e3\u3059\u308b\u8a00\u8a9e\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u3092\u76ee\u7684\u3068\u3057\u305f\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u5b66\u7fd2\u306b\u304a\u3051\u308b\u691c\u8a3c\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        31. \u6a2a\u5ddd\u60a0\u9999\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u4fee\u8f9e\u69cb\u9020\u3068\u8a9e\u5f59\u96e3\u6613\u5ea6\u3092\u5236\u5fa1\u53ef\u80fd\u306a\u30c6\u30ad\u30b9\u30c8\u751f\u6210\u624b\u6cd5\u306b\u5411\u3051\u3066\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        32. \u5713\u7530\u5f69\u4e43\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u5185\u90e8\u6319\u52d5\u306e\u8a00\u8a9e\u5316\u3092\u901a\u3058\u305f\u5236\u5fa1\u624b\u6cd5\u306e\u69cb\u7bc9\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        33. \u6728\u6751\u9ebb\u53cb\u5b50\uff0cLis Kanashiro Pereira\uff0c\u6d45\u539f\u6b63\u5e78\uff0cFei Cheng\uff0c\u8d8a\u667a\u7dbe\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u6642\u9593\u95a2\u4fc2\u30bf\u30b9\u30af\u3092\u5bfe\u8c61\u306b\u3057\u305f\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u5b66\u7fd2\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u306e\u89aa\u548c\u6027\u306e\u89e3\u6790\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        34. \u9808\u85e4\u767e\u9999\uff0c\u5c0f\u51fa(\u9593\u5cf6)\u76f4\u5b50\uff0c\u6d45\u539f\u6b63\u5e78\uff0c\u5c71\u53e3\u88d5\u4eba\uff0c\u4e45\u4fdd\u7406\u6075\u5b50\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u30d2\u30c8\u8133\u306b\u304a\u3051\u308b\u6642\u9593\u8a8d\u8b58\u6642\u306e\u8133\u5185\u72b6\u614b\u306e\u63a8\u5b9a\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        35. \u6e21\u908a\u6e05\u5b50\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u30c8\u30ec\u30fc\u30b9\u304b\u3089\u30e6\u30fc\u30b6\u306e\u610f\u56f3\u3092\u53cd\u6620\u3057\u305f\u753b\u50cf\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        36. Muxuan Liu\uff0c\u77f3\u57a3\u9054\u4e5f\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u793e\u4f1a\u7684\u72b6\u6cc1\u306b\u57fa\u3065\u3044\u305f\u65e5\u672c\u8a9e\u30d3\u30b8\u30cd\u30b9\u30e1\u30fc\u30eb\u30b3\u30fc\u30d1\u30b9\u306e\u69cb\u7bc9\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        37. \u7f85 \u685c\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8133\u5185\u72b6\u614b\u63a8\u5b9a\u306e\u305f\u3081\u306e\u6c4e\u7528\u8a00\u8a9e\u30e2\u30c7\u30eb\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li>
                        38. \u6751\u5c71\u53cb\u7406\uff0c\u5c0f\u6797\u4e00\u90ce\uff0e\u300c\u8a18\u61b6\u88c5\u7f6e\u4ed8\u304d\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u30e2\u30c7\u30eb\u306b\u3088\u308b\u69cb\u9020\u5316\u77e5\u8b58\u3068\u6f14\u7b97\u51e6\u7406\u3092\u7528\u3044\u305f\u8cea\u554f\u5fdc\u7b54\u300d\uff0e\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a(NLP2023)\uff0c\u6c96\u7e04\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u6c96\u7e04\uff0c2023\u5e743\u6708\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                          \n\n\n\n

                          2022<\/h2>\n\n\n\n

                          <\/i> Journal<\/h3>\n\n\n\n
                          1. Kana Ozaki, Ichiro Kobayashi. “A Study on Stochastic Variational Inference for Topic Modeling with Word Embeddings”. Computaci\u00f3n y Sistemas, Vol. 26, No. 3, pp. 1225\u20131232, 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                            Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                            1. Masatoshi Nagano, Tomoaki Nakamura, Takayuki Nagai, Daichi Mochihashi, Ichiro Kobayashi. “Spatio-temporal categorization for first-person-view videos using a convolutional variational autoencoder and Gaussian processes”, Frontiers in Robotics and AI, Vol. 9, 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                              <\/i> International Conference<\/h3>\n\n\n\n
                              1. Chihiro Maru, Boris Brandherm, and Ichiro Kobayashi. \u201cVerification of Sparsity in the Attention Mechanism of Transformer for Anomaly Detection in Multivariate Time Series\u201d, short paper, 2022 IEEE International Conference on BigData(IEEE BigData 2022), Osaka, Japan, Dec. 2022. <\/i><\/a><\/li>
                              2. Ayano Enta and Ichiro Kobayashi. “Building a Control Method through Verbalizing the Internal Behavior of a Deep Reinforcement Learning Model”. Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), Mie, Japan, Nov. 2022. <\/i><\/a><\/li>
                              3. Mayuko Kimura, Lis Kanashiro Pereira and Ichiro Kobayashi. “Effective Masked Language Modeling for Temporal Commonsense Reasoning”. Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), Mie, Japan, Nov. 2022. <\/i><\/a><\/li>
                              4. Haruka Taguchi, Satoshi Nishida, Shinji Nishimoto, and Ichiro Kobayashi. “Validation of the Role of Attention Mechanism in Predicting Brain Activity”. Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), Mie, Japan, Nov. 2022. <\/i><\/a><\/li>
                              5. Sayako Watanabe and Ichiro Kobayashi. “Image Generation reflecting the Meaning of Language that reveals Object’s Attributes”. Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), Mie, Japan, Nov. 2022. <\/i><\/a><\/li>
                              6. Yuri Murayama and Ichiro Kobayashi. “Towards Question Answering with Multi-hop Reasoning over Knowledge using a Neural Network Model with External Memories”. Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), Mie, Japan, Nov. 2022. <\/i><\/a><\/li>
                              7. <\/i> Chihiro Maru, Boris Brandherm, and Ichiro Kobayashi. “Combining Transformer with a Discriminator for Anomaly Detection in Multivariate Time Series”. Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), Mie, Japan, Nov. 2022. Best Paper Award<\/a>. <\/i><\/a><\/li>
                              8. Haruka Kawasaki, Satoshi Nishida, and Ichiro Kobayashi. “Hierarchical Processing of Visual and Language Information in the Brain”. short paper (Findings), The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing(AACL-IJCNLP2022), Taipei, Taiwan, Nov. 2022. <\/i><\/a><\/li>
                              9. Mayuko Kimura, Lis Kanashiro Pereira, and Ichiro Kobayashi. “Toward Building a General-Purpose Language Model for Understanding Temporal Commonsense”. AACL-IJCNLP2022 Student Research Workshop, Taipei, Taiwan, Nov. 2022. <\/i><\/a><\/li>
                              10. Sayako Watanabe and Ichiro Kobayashi. “Caption Generation Reflecting the Intent of the Explainer by Tracing on an Image”. AACL-IJCNLP2022 Student Research Workshop, Taipei, Taiwan, Nov. 2022.<\/li>
                              11. Lis Kanashiro Pereira, Kevin Duh, Fei Cheng, Masayuki Asahara, and Ichiro Kobayashi. “Attention-Focused Adversarial Training for Robust Temporal Reasoning”. The European Language Resources Association (LREC) 2022, Marseille, France, Jun. 2022. <\/i><\/a><\/li>
                              12. Muxuan Liu and Ichiro Kobayashi. “Construction and Validation of a Japanese Honorific Corpus Based on Systemic Functional Linguistics, Workshop on Dataset Creation for Lower-Resourced Languages”. Proceedings of the 1st Workshop on Dataset Creation for Lower-Resourced Languages (DCLRL) @LREC2022. Marseille, France, Jun. 2022. <\/i><\/a><\/li>
                              13. Lis Kanashiro Pereira and Ichiro Kobayashi. “OCHADAI at SemEval-2022 Task 2: Adversarial Training for Multilingual Idiomaticity Detection”. SemEval-2022: 15th International Workshop on Semantic Evaluation, The 2022 Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL-HLT 2022), Seattle, U.S.A., Jul. 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                                1. Edison Marrese-Taylor, Yumi Hamazono, Tatsuya Ishigaki, Goran Topic, Yusuke Miyao, Ichiro Kobayashi, Hiroya Takamura. “Open-domain Video Commentary Generation”, The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP2022), Abu Dhabi, UAE, Dec. 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                  <\/i> Preprint<\/strong><\/h3>\n\n\n\n
                                  1. Lis Kanashiro Pereira, Ichiro Kobayashi. “OCHADAI at SemEval-2022 Task 2: Adversarial Training for Multilingual Idiomaticity Detection”, arXiv, 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                    Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                                    1. Erica K. Shimomoto, Edison Marrese-Taylor, Hiroya Takamura, Ichiro Kobayashi, Hideki Nakayama, Yusuke Miyao. “Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video Grounding”, arXiv, 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                      <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                                      1. <\/i> \u7530\u53e3 \u9065\u9999\uff0c\u897f\u7530 \u77e5\u53f2\uff0c\u897f\u672c \u4f38\u5fd7\uff0c\u5c0f\u6797 \u4e00\u90ce\uff0e\u300c\u8133\u5185\u72b6\u614b\u63a8\u5b9a\u306b\u304a\u3051\u308b\u6ce8\u610f\u6a5f\u69cb\u306e\u5f79\u5272\u306e\u691c\u8a3c\u300d\uff0c\u7b2c38\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u6771\u4eac\u90fd\u7acb\u7523\u696d\u6280\u8853\u5927\u5b66\u9662\u5927\u5b66\uff0c\u6771\u4eac\uff0c2022\u5e749\u6708\uff0eFuzzy Special Session Presentation Award<\/a>.<\/li>
                                      2. \u5ca9\u4e95 \u9065\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u4f4e\u6b21\u6a5f\u80fd\u3092\u878d\u5408\u3059\u308b\u767a\u9054\u578b\u4eba\u5de5\u795e\u7d4c\u56de\u8def\u7db2\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708. <\/i><\/a><\/li>
                                      3. \u5ddd\ufa11 \u6625\u4f73\uff0c\u897f\u7530 \u77e5\u53f2\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u30d2\u30c8\u8133\u5185\u306b\u304a\u3051\u308b\u8996\u899a\u30fb\u8a00\u8a9e\u60c5\u5831\u306e\u968e\u5c64\u7684\u51e6\u7406\u306e\u89e3\u660e\u3078\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708. <\/i><\/a><\/li>
                                      4. \u6210\u7530 \u767e\u82b1\uff0c\u8c37\u53e3 \u5df4\uff0c\u6301\u6a4b \u5927\u5730\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6728\u69cb\u9020Transformer\u3092\u7528\u3044\u305f\u6559\u5e2b\u3042\u308a\u7d71\u8a9e\u69cb\u9020\u89e3\u6790\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      5. \u8239\u66f3 \u65e5\u4f73\u91cc\uff0c\u6728\u6751 \u9ebb\u53cb\u5b50\uff0cKanashiro Pereira Lis\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6642\u9593\u7684\u5e38\u8b58\u3092\u8a8d\u8b58\u3059\u308b\u65e5\u672c\u8a9e\u6c4e\u7528\u8a00\u8a9e\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708<\/i><\/a><\/li>
                                      6. \u6a2a\u5ddd \u60a0\u9999\uff0c\u5c0f\u6797 \u4e00\u90ce. \u300c\u30c8\u30d4\u30c3\u30af\u306b\u57fa\u3065\u304f\u62bd\u8c61\u578b\u8981\u7d04\u6587\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      7. \u5713\u7530 \u5f69\u4e43\uff0c\u5c0f\u6797 \u4e00\u90ce. \u5b66\u7fd2\u6e08\u307f\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u5185\u90e8\u6319\u52d5\u3092\u6a21\u3057\u305f\u30d5\u30a1\u30b8\u30a3\u5236\u5fa1\u5668\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      8. \u6728\u6751 \u9ebb\u53cb\u5b50\uff0cKanashiro Pereira Lis\uff0c\u6d45\u539f \u6b63\u5e78\uff0cCheng Fei\uff0c\u8d8a\u667a \u7dbe\u5b50\uff0c\u5c0f\u6797 \u4e00\u90ce. \u300c\u6642\u9593\u7684\u5e38\u8b58\u7406\u89e3\u3078\u5411\u3051\u305f\u8a00\u8a9e\u30e2\u30c7\u30eb\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      9. \u9808\u85e4 \u767e\u9999\uff0c\u5c0f\u51fa(\u9593\u5cf6) \u771f\u5b50\uff0c\u6d45\u539f \u6b63\u5e78\uff0c\u5c71\u53e3 \u88d5\u4eba\uff0c\u4e45\u4fdd \u7406\u6075\u5b50\uff0c\u897f\u672c \u4f38\u5fd7\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300cDVD\u9451\u8cde\u523a\u6fc0\u4e0b\u306e\u8133\u6d3b\u52d5\u306b\u304a\u3051\u308b\u6642\u9593\u8a8d\u8b58\u72b6\u614b\u306e\u63a8\u5b9a\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      10. <\/i> \u6e21\u908a \u6e05\u5b50\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u30da\u30f3\u5148\u306e\u8ecc\u8de1\u304b\u3089\u8aac\u660e\u8005\u306e\u610f\u56f3\u3092\u53cd\u6620\u3057\u305f\u753b\u50cf\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u300d.\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0eJSAI Annual Conference Award<\/a>. <\/i><\/a><\/li>
                                      11. Muxuan LIU\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u793e\u4f1a\u7684\u95a2\u4fc2\u3092\u8003\u616e\u3057\u305f\u65e5\u672c\u8a9e\u656c\u8a9e\u30b3\u30fc\u30d1\u30b9\u306e\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d.\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      12. \u9ed2\u7530 \u5f57\u8389\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u753b\u50cf\u5185\u306e\u7269\u4f53\u306b\u7740\u76ee\u3057\u305f\u52d5\u304d\u306e\u5909\u5316\u70b9\u62bd\u51fa\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      13. \u9685\u7530 \u8389\u9999\u5b50\uff0c\u5c71\u53e3 \u88d5\u4eba\uff0c\u4e2d\u4e95 \u667a\u4e5f\uff0c\u897f\u672c \u4f38\u5fd7\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u4e88\u6e2c\u8133\u6d3b\u52d5\u3092\u5bfe\u8c61\u306b\u3057\u305f\u6c4e\u7528\u8a00\u8a9e\u30e2\u30c7\u30eb\u3068\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u691c\u8a3c\u300d.\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      14. \u7f85 \u685c\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6c4e\u7528\u8a00\u8a9e\u30e2\u30c7\u30ebBrainBERT\u3092\u7528\u3044\u305f\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u8133\u5185\u72b6\u614b\u63a8\u5b9a\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c36\u56de\uff09\uff0c\u56fd\u7acb\u4eac\u90fd\u56fd\u969b\u4f1a\u9928\uff0c\u4eac\u90fd\uff0c2022\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                      15. \u6728\u6751 \u9ebb\u53cb\u5b50\uff0cLis Kanashiro Pereira\uff0c\u6d45\u539f \u6b63\u5e78\uff0cFei Cheng\uff0c\u8d8a\u667a \u7dbe\u5b50\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6642\u9593\u7684\u5e38\u8b58\u7406\u89e3\u3078\u5411\u3051\u305f\u52b9\u679c\u7684\u306a\u30de\u30b9\u30af\u8a00\u8a9e\u30e2\u30c7\u30eb\u306e\u691c\u8a3c\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      16. \u6e21\u908a \u6e05\u5b50\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u30c8\u30ec\u30fc\u30b9\u306b\u3088\u308a\u753b\u50cf\u306e\u6ce8\u8996\u70b9\u3092\u4e0e\u3048\u308b\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30c6\u30ad\u30b9\u30c8\u751f\u6210\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      17. Muxuan LIU\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u9078\u629e\u4f53\u7cfb\u6a5f\u80fd\u8a00\u8a9e\u5b66\u306b\u57fa\u3065\u304f\u65e5\u672c\u8a9e\u656c\u8a9e\u30b3\u30fc\u30d1\u30b9\u306e\u69cb\u7bc9\u3068\u691c\u8a3c\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      18. \u6298\u53e3 \u5e0c\u5b9f\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6575\u5bfe\u7684\u30b5\u30f3\u30d7\u30eb\u3092\u7528\u3044\u305f\u5bfe\u7167\u5b66\u7fd2\u306e\u6027\u80fd\u5411\u4e0a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      19. \u8c37\u53e3 \u5df4\uff0c\u4e0a\u539f \u6cc9\uff0c\u5ddd\u5d0e \u91c7\u9999\uff0c\u6d45\u539f \u6b63\u5e78\uff0c\u9152\u4e95 \u88d5\uff0c\u8d8a\u667a \u7dbe\u5b50\uff0c\u5c0f\u6797 \u4e00\u90ce. \u300c\u30c8\u30d4\u30c3\u30af\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u5e74\u4ee3\u5225\u4f5c\u6587\u306e\u6642\u9593\u306b\u95a2\u3059\u308b\u8a8d\u8b58\u306e\u5206\u6790\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      20. \u7530\u5c4b \u4f91\u5e0c\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u5358\u8a9e\u57cb\u3081\u8fbc\u307f\u306b\u52b9\u679c\u7684\u306a\u30ce\u30a4\u30ba\u306e\u691c\u8a3c\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      21. \u8c37\u53e3 \u5df4\uff0c\u6301\u6a4b \u5927\u5730\uff0c\u9577\u91ce \u5321\u96bc\uff0c\u4e2d\u6751 \u53cb\u662d\uff0c\u9577\u4e95 \u9686\u884c\uff0c\u7a32\u9091 \u54f2\u4e5f\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u30ac\u30a6\u30b9\u904e\u7a0b\u3092\u7528\u3044\u305f\u5468\u6ce2\u6570\u30b9\u30da\u30af\u30c8\u30eb\u5206\u6790\u306b\u3088\u308b\u526f\u8a5e\u306e\u7406\u89e3\u300d. \u30d1\u30bf\u30fc\u30f3\u8a8d\u8b58\u30fb\u30e1\u30c7\u30a3\u30a2\u7406\u89e3\u7814\u7a76\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3 \uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      22. \u4e0a\u6751 \u548c\u8cb4\u5b50\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u60a3\u8005\u3078\u306e\u533b\u7642\u51e6\u7f6e\u306b\u5bfe\u3059\u308b\u5f37\u5316\u5b66\u7fd2\u9069\u7528\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c84\u56de\u5168\u56fd\u5927\u4f1a, \u611b\u5a9b\u5927\u5b66\u57ce\u5317\u30ad\u30e3\u30f3\u30d1\u30b9\uff08\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u958b\u50ac\uff09\uff0c2022\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                      23. <\/i> \u9ed2\u7530 \u5f57\u8389\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u7269\u7406\u74b0\u5883\u306b\u304a\u3051\u308b\u5909\u5316\u70b9\u62bd\u51fa\u306e\u53d6\u308a\u7d44\u307f\u300d. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c84\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u611b\u5a9b\u5927\u5b66\u57ce\u5317\u30ad\u30e3\u30f3\u30d1\u30b9\uff08\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u958b\u50ac\uff09\uff0c2022\u5e743\u6708\uff0eStudent Encouragement Award of IPSJ National Convention<\/a>\uff0e<\/i><\/a><\/li>
                                      24. \u5ddd\ufa11 \u6625\u4f73\uff0c\u897f\u7530 \u77e5\u53f2\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u8133\u5185\u306b\u304a\u3051\u308b\u8996\u899a\u30fb\u610f\u5473\u60c5\u5831\u306e\u968e\u5c64\u7684\u51e6\u7406\u306e\u89e3\u660e\u3078\u5411\u3051\u305f\u53d6\u308a\u7d44\u307f\u300d. \u30cb\u30e5\u30fc\u30ed\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u7814\u7a76\u4f1a\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2022\u5e741\u6708\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                                        \n
                                        \n<\/div><\/div>\n\n\n\n

                                        2021<\/h2>\n\n\n\n

                                        <\/i> Journal<\/h3>\n\n\n\n
                                        1. Ichiro Kobayashi. “Intelligence of Artificial Intelligence: A Study on Brain Decoding using Machine Learning and the Analysis of Brain Functions”. Japanese Journal of Neurosurgery, Vol. 30, No. 2, pp. 120-127, 2021. <\/i><\/a><\/li>
                                        2. Kasumi Aoki, Akira Miyazawa, Tatsuya Ishigaki, Tatsuya Aoki, Hiroshi Noji, Keiichi Goshima,Hiroya Takamura, Yusuke Miyao, Ichiro Kobayashi. “Controlling contents in data-to-document generation with human-designed topic labels”. Proceedings of the 12th International Conference on Natural Language Generation, pp. 323-332, 2021. <\/i><\/a><\/li>
                                        3. Ichiro Kobayashi. “Towards Real World Simulation by Natural Language”. Journal of the Robotics Society of Japan, Vol. 39, Issue 5, pp. 391-398, 2021. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                          <\/i> International Conference<\/h3>\n\n\n\n
                                          1. <\/i> Nozomi Origuchi and Ichiro Kobayashi. “Continuous Transformation of Neural Language Syntactic Structure using Grammar Variational Autoencoder”. The 22nd International Symposium on Advanced Intelligent Systems, Online, Dec. 2021. Best Session Award<\/mark>.<\/li>
                                          2. <\/i> Eri Kuroda, Shinji Nishimoto, Satoshi Nishida, and Ichiro Kobayashi. “A Deep Generative Model imitating Predictive Coding in the Human Brain”. The 22nd International Symposium on Advanced Intelligent Systems, Online, Dec. 2021. Best Session Award<\/mark>.<\/li>
                                          3. Rikako Sumida, Hiroto Yamaguchi, Tomoya Nakai, Shinji Nishimoto and Ichiro Kobayashi. “Comparison of Language Processing Active Areas by Estimating Brain Activities evoked by Listening and Reading”. The 22nd International Symposium on Advanced Intelligent Systems, Online, Dec. 2021.<\/li>
                                          4. <\/i> Luo Ying and Ichiro Kobayashi. “BrainBERT: A Language Model Capturing the Correspondence between Brain Activities and Language”. The 22nd International Symposium on Advanced Intelligent Systems, Online, Dec. 2021. Best Presentation Award<\/mark>.<\/li>
                                          5. Lis Kanashiro Pereira, Yuki Taya, and Ichiro Kobayashi. “Multi-Layer Random Perturbation Training for improving Model Generalization Efficiently”. Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackBoxNLP), Online, Nov. 2021. <\/i><\/a><\/li>
                                          6. Chenjing Geng, Fei Cheng, Masayuki Asahara, Lis Kanashiro Pereira, and Ichiro Kobayashi. “Dependency Enhanced Contextual Representations for Japanese Temporal Relation Classification”. The 35th Pacific Asia Conference on Language, Information and Computation (PACLIC35), Online, Nov. 2021. <\/i><\/a><\/li>
                                          7. Yumi Hamazono, Tatsuya Ishigaki, Ichiro Kobayashi, Yusuke Miyao and Hiroya Takamura. “Unpredictable Attributes in Data-to-text Generation”. The 35th Pacific Asia Conference on Language, Information and Computation (PACLIC35), Online, Nov. 2021. <\/i><\/a><\/li>
                                          8. Lis Kanashiro Pereira, Fei Cheng, Masayuki Asahara, and Ichiro Kobayashi. “ALICE++: Adversarial Training for Robust and Effective Temporal Reasoning”. The 35th Pacific Asia Conference on Language, Information and Computation (PACLIC35), Online, Nov. 2021. <\/i><\/a><\/li>
                                          9. Sumida Rikako, Hiroto Yamaguchi, Tomoya Nakai, Shinji Nishimoto, and Ichiro Kobayashi. “Comparison of active areas by estimating brain activities evoked by verbal stimuli given from speech and text”. The 2021 International Conference on Brain Informatics (BI21), Online, Sep. 2021.<\/li>
                                          10. Mayuko Kimura, Lis Kanashiro Pereira, and Ichiro Kobayashi. “Towards a Language Model for Temporal Commonsense Reasoning”. Proceedings of the Student Research Workshop Associated with RANLP 2021, International Conference Recent Advances in Natural Language Processing (RANLP2021), Online, Sep. 2021. <\/i><\/a><\/li>
                                          11. <\/i> Yuki Taya, Lis Kanashiro Pereira, Fei Cheng, Ichiro Kobayashi. “OCHADAI-KYODAI at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction”. Workshop of SemEval 2021 (ACL-IJCNL2021), Online, Aug. 2021. Honorable Mention<\/a>. <\/i><\/a><\/li>
                                          12. Ying Luo, Lis Kanashiro Pereira, Ichiro Kobayashi. “OCHADAI at SMM4H-2021 Task 5: Classifying self-reporting tweets on potential cases of COVID-19 by ensembling pre-trained language models”. Workshop of SMM4H 2021 (NAACL2021), Online, Jun. 2021. <\/i><\/a><\/li>
                                          13. Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, and Ichiro Kobayashi. “Targeted Adversarial Training for Natural Language Understanding”. 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics(NAACL2021), Online, Jun. 2021. <\/i><\/a> <\/i><\/a><\/li><\/ol>\n\n\n\n

                                            Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                                            1. Tatsuya Ishigaki, Goran Topic, Yumi Hamazono, Hiroshi Noji, Ichiro Kobayashi, Yusuke Miyao, Hiroya Takamura. “Generating Racing Game Commentary from Vision, Language, and Structured Data”, The 14th International Conference on Natural Language Generation (INLG 2021), Aberdeen, United Kingdom, Sep. 2021. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                              <\/i> Preprint<\/strong><\/h3>\n\n\n\n
                                              1. Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi. “Targeted Adversarial Training for Natural Language Understanding”, arXiv, 2022. <\/i><\/a><\/li>
                                              2. Yuki Taya, Lis Kanashiro Pereira, Fei Cheng, Ichiro Kobayashi. “OCHADAI-KYODAI at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction”, arXiv, 2022. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                                                1. \u9808\u85e4\u767e\u9999\uff0c\u5c0f\u51fa\uff08\u9593\u5cf6\uff09\u76f4\u5b50\uff0c\u6d45\u539f\u6b63\u5e78\uff0c\u5c71\u53e3\u88d5\u4eba\uff0c\u4e45\u4fdd\u7406\u6075\u5b50\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u52d5\u753b\u50cf\u8996\u8074\u6642\u306e\u8a00\u8a9e\u523a\u6fc0\u304b\u3089\u306e\u8133\u6d3b\u52d5\u72b6\u614b\u63a8\u5b9a\u306b\u304a\u3051\u308b\u4e00\u8003\u5bdf\u300d. \u7b2c37\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                2. \u7530\u53e3\u9065\u9999\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u753b\u50cf\u523a\u6fc0\u4e0b\u306e\u8133\u6d3b\u52d5\u72b6\u614b\u63a8\u5b9a\u306b\u304a\u3051\u308b\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u57fa\u790e\u7684\u8003\u5bdf\u300d. \u7b2c37\u56de \u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                3. <\/i> \u9685\u7530\u8389\u9999\u5b50\uff0c\u5c71\u53e3\u88d5\u4eba\uff0c\u4e2d\u4e95\u667a\u4e5f\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u8074\u899a\u3068\u8996\u899a\u304b\u3089\u306a\u308b\u8a00\u8a9e\u523a\u6fc0\u4e0b\u306e\u8133\u6d3b\u52d5\u72b6\u614b\u63a8\u5b9a\u306b\u3088\u308b\u6d3b\u52d5\u9818\u57df\u306e\u6bd4\u8f03\u300d. \u7b2c37\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e749\u6708\uff0e\u30dd\u30b9\u30bf\u30fc\u30fb\u30c7\u30e2\u30bb\u30c3\u30b7\u30e7\u30f3\u6700\u512a\u79c0\u8cde<\/mark>. <\/i><\/a><\/li>
                                                4. \u5713\u7530\u5f69\u4e43\uff0cLis Kanashiro Pereira\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u5185\u90e8\u6319\u52d5\u306e\u8a00\u8a9e\u5316\u306b\u3088\u308b\u5236\u5fa1\u624b\u6cd5\u69cb\u7bc9\u3078\u5411\u3051\u3066.\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c35\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                5. \u6e21\u908a\u6e05\u5b50\uff0cLis Kanashiro Pereira\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u7279\u6027\u3092\u9855\u5728\u5316\u3059\u308b\u8a00\u8a9e\u306e\u610f\u5473\u3092\u53cd\u6620\u3057\u305f\u753b\u50cf\u751f\u6210\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c35\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                6. \u5b6b\u5ef6\u541b\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u753b\u50cf\u3092\u901a\u3058\u305f\u540c\u7fa9\u6587\u306e\u6f5c\u5728\u7a7a\u9593\u306b\u304a\u3051\u308b\u5bfe\u5fdc\u95a2\u4fc2\u306e\u5b66\u7fd2. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c35\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e746\u6708. <\/i><\/a><\/li>
                                                7. \u7f85 \u685c\uff0c\u5c0f\u6797\u4e00\u90ce.\u300cBrainBERT\uff1a\u8133\u6d3b\u52d5\u3068\u30c6\u30ad\u30b9\u30c8\u306e\u5bfe\u5fdc\u95a2\u4fc2\u3092\u6349\u3048\u305f\u8a00\u8a9e\u30e2\u30c7\u30eb\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c37\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                8. \u6728\u6751\u9ebb\u53cb\u5b50\uff0cLis Kanashiro Pereira\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6642\u9593\u7684\u5e38\u8b58\u3092\u7406\u89e3\u3059\u308b\u8a00\u8a9e\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u3078\u5411\u3051\u3066\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u6d5c\u677e\uff08\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u958b\u50ac\uff09\uff0c2021\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                9. \u6298\u53e3\u5e0c\u5b9f\uff0cLis Kanashiro Pereira\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6587\u6cd5\u5909\u5206\u81ea\u5df1\u7b26\u53f7\u5316\u5668\u3092\u7528\u3044\u305f\u7d71\u8a9e\u69cb\u9020\u306e\u9023\u7d9a\u7684\u5909\u63db\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u6d5c\u677e\uff08\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u958b\u50ac\uff09\uff0c2021\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                10. \u8c37\u53e3\u5df4\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u9577\u91ce\u5321\u96bc\uff0c\u4e2d\u6751\u53cb\u662d\uff0c\u9577\u4e95\u9686\u884c\uff0c\u9ad8\u91ce\u6e09\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u30b9\u30da\u30af\u30c8\u30eb\u6df7\u5408\u30ab\u30fc\u30cd\u30eb\u3068\u30ac\u30a6\u30b9\u904e\u7a0b\u306b\u57fa\u3065\u304f\u52d5\u753b\u304b\u3089\u306e\u526f\u8a5e\u306e\u610f\u5473\u7406\u89e3\u300d. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\uff0c\u6d5c\u677e\uff08\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u958b\u50ac\uff09\uff0c2021\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                11. \u9ed2\u7530\u5f57\u8389\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4e88\u6e2c\u7b26\u53f7\u5316\u3092\u6a21\u5023\u3059\u308b\u6df1\u5c64\u751f\u6210\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u306b\u5411\u3051\u305f\u57fa\u790e\u7684\u691c\u8a0e\u300d. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c83\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2021\u5e743\u6708\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                                                  \n\n\n\n

                                                  2020<\/h2>\n\n\n\n

                                                  <\/i> Journal<\/h3>\n\n\n\n
                                                  1. Yumi Hamazono, Ichiro Kobayashi, Hideki Asoh, Tomoaki Nakamura, Takayuki Nagai, and Daichi Mochihashi. “Motion Generation Using Humanoid Robot with Language Understanding”. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol.32, No.1, pp.1-11, 2020. <\/i><\/a><\/li>
                                                  2. Chihiro Maru, and Ichiro Kobayashi.\u300c\u6575\u5bfe\u7684\u751f\u6210\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u96c6\u56e3\u578b\u7570\u5e38\u691c\u77e5\u300d. DBSJ Japanese Journal, Vol.18-J, No. 2, 2020. <\/i><\/a><\/li>
                                                  3. Nana Otawara, Akari Inago, Hiroshi Tsukahara, and Ichiro Kobayashi. “Understanding Natural Language Instructions for Self-Driving Cars and Grounding”. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol. 32, pp. 722-736, 2020. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                    <\/i> International Conference<\/h3>\n\n\n\n
                                                    1. Chihiro Maru and Ichiro Kobayashi. “Collective Anomaly Detection for Multivariate Data using Generative Adversarial Networks”. The 2020 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, U.S.A., Dec. 2020. <\/i><\/a><\/li>
                                                    2. Yumi Hamazono, Yui Uehara, Hiroshi Noji, Yusuke Miyao, Hiroya Takamura, Ichiro Kobayashi. “Market Comment Generation from Data with Noisy Alignments”. The International Conference on Natural Language Generation (INLG 2020), Online, Dec. 2020. <\/i><\/a><\/li>
                                                    3. Yuri Murayama, Lis Kanashiro Pereira, and Ichiro Kobayashi. \u201cDialogue over context and structured knowledge using a neural network model with external memories.\u201d In Proceedings of Knowledgeable NLP: the First Workshop on Integrating Structured Knowledge and Neural Networks for NLP, pp. 11-20, Online, Dec. 2020. <\/i><\/a><\/li>
                                                    4. Lis Pereira, Xiaodong Liu, Fei Cheng, Masayuki Asahara, Ichiro Kobayashi. “Adversarial Training for Commonsense Inference”. Proceedings of the 5th Workshop on Representation Learning for NLP (RepL4NLP-2020), pages 55\u201360, July 9, 2020. Association for Computational Linguistics 2020, Online, Jul. 2020. <\/i><\/a> <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                      Prof. Kobayashi with collaborators<\/h4>\n\n\n\n
                                                      1. Fei Cheng, Masayuki Asahara, Ichiro Kobayashi, Sadao Kurohashi. “Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning”, The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), Findings, Online, Nov. 2020. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                        <\/i> Preprint<\/strong><\/h3>\n\n\n\n
                                                        1. Lis Pereira, Xiaodong Liu, Fei Cheng, Masayuki Asahara, Ichiro Kobayashi. “Adversarial Training for Commonsense Inference”, arXiv, 2020. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                          <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                                                          1. \u9ed2\u7530\u5f57\u8389\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4e88\u6e2c\u7b26\u53f7\u5316\u3092\u6a21\u5023\u3059\u308b\u6df1\u5c64\u751f\u6210\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u306b\u5411\u3051\u305f\u53d6\u308a\u7d44\u307f\u300d. \u7b2c23\u56de\u60c5\u5831\u8ad6\u7684\u5b66\u7fd2\u7406\u8ad6\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e7411\u6708\uff0e<\/li>
                                                          2. \u6298\u53e3\u5e0c\u5b9f\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6587\u6cd5\u5909\u5206\u81ea\u5df1\u7b26\u53f7\u5316\u5668\u3092\u7528\u3044\u305f\u81ea\u7136\u8a00\u8a9e\u6587\u306e\u9023\u7d9a\u7684\u306a\u7d71\u8a9e\u69cb\u9020\u5909\u63db \u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          3. \u9ed2\u7530\u5f57\u8389\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u30d2\u30c8\u8133\u5185\u3067\u306e\u4e88\u6e2c\u3092\u5bfe\u8c61\u3068\u3059\u308b\u6df1\u5c64\u751f\u6210\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          4. \u8c37\u53e3\u5df4\uff0c\u9577\u91ce\u5321\u96bc\uff0c\u6301\u6a4b\u5927\u5730\uff0c\u4e2d\u6751\u53cb\u662d\uff0c\u9ad8\u91ce\u6e09\uff0c\u9577\u4e95\u9686\u884c\uff0c\u5c0f\u6797\u4e00\u90ce.\u300cSpectral Mixture Kernel\u3092\u7528\u3044\u305f\u52d5\u4f5c\u3092\u8868\u3059\u526f\u8a5e\u306e\u610f\u5473\u7406\u89e3\u3078\u5411\u3051\u305f\u53d6\u308a\u7d44\u307f \u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          5. \u7530\u5c4b\u4f91\u5e0c\uff0c\u6b05\u60c7\u5fd7\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u753b\u50cf\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u306b\u304a\u3051\u308b\u30b7\u30fc\u30f3\u30b0\u30e9\u30d5\u7279\u5fb4\u91cf\u52b9\u679c\u691c\u8a3c\u306e\u305f\u3081\u306e\u30e6\u30fc\u30b6\u30b9\u30bf\u30c7\u30a3\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          6. \u5ee3\u7530\u68a8\u90a3\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u304a\u3051\u308b\u6ce8\u610f\u6a5f\u69cb\u306b\u5bfe\u3059\u308b\u4e00\u8003\u5bdf\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          7. \u803f\u6668\u30bb\u30a4\uff0c\u7a0b \u98db\uff0cLis Kanashiro Pereira\uff0c\u6d45\u539f\u6b63\u5e78\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4f9d\u5b58\u95a2\u4fc2\u3068\u6587\u8108\u8868\u73fe\u3092\u7528\u3044\u305f\u65e5\u672c\u8a9e\u6642\u9593\u95a2\u4fc2\u8b58\u5225 \u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          8. \u5927\u7530\u539f\u83dc\u3005\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u6b05 \u60c7\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u8eca\u3092\u5bfe\u8c61\u3068\u3059\u308b\u69d8\u3005\u306a\u99d0\u8eca\u6307\u793a\u306e\u7a7a\u9593\u610f\u5473\u8868\u73fe\u306b\u57fa\u3065\u304f\u30b0\u30e9\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          9. \u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4e8b\u524d\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u8981\u7d04\u30e2\u30c7\u30eb\u3078\u306e\u6f5c\u5728\u30c8\u30d4\u30c3\u30af\u5c0e\u5165\u306b\u3088\u308b\u52b9\u679c\u306e\u691c\u8a3c\u300d.\u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          10. \u6751\u5c71\u53cb\u7406\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u8a18\u61b6\u88c5\u7f6e\u4ed8\u304d\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u30e2\u30c7\u30eb\u306b\u3088\u308b\u6587\u8108\u3068\u69cb\u9020\u5316\u77e5\u8b58\u3092\u7528\u3044\u305f\u5bfe\u8a71\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          11. \u6ff1\u5712\u4f91\u7f8e\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u80fd\u5730\u5b8f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u52d5\u5411\u8aac\u660e\u6587\u751f\u6210\u306b\u304a\u3051\u308b\u53c2\u7167\u6642\u523b\u306e\u4e0d\u6574\u5408\u89e3\u6d88\u306e\u7cbe\u5ea6\u5411\u4e0a\u306b\u5411\u3051\u305f\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c34\u56de\uff09\uff0c\u30aa\u30f3\u30e9\u30a4\u30f3\uff0c2020\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                          12. \u7530\u5c4b\u4f91\u5e0c\uff0c\u6b05\u60c7\u5fd7\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u753b\u50cf\u30ad\u30e3\u30d7\u30b7\u30e7\u30f3\u751f\u6210\u306b\u304a\u3051\u308b\u30b7\u30fc\u30f3\u30b0\u30e9\u30d5\u7279\u5fb4\u91cf\u306e\u52b9\u679c\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          13. \u5cf6\u767e\u5b50\uff0c\u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u30b9\u30d1\u30fc\u30b9\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u3092\u7528\u3044\u305f\u8133\u5185\u610f\u5473\u8868\u8c61\u63a8\u5b9a\u306b\u304a\u3051\u308bBERT\u306e\u6709\u52b9\u6027\u306e\u691c\u8a3c\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          14. Chenjing Geng, Lis Kanashiro Pereira, Fei Cheng, Masayuki Asahara, and Ichiro Kobayashi. “Dependency Enhanced Contextual Representations for Japanese Temporal Relation Classification”. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          15. \u6f06\u539f\u7406\u4e43\uff0c\u5c71\u53e3\u88d5\u4eba\uff0c\u4e2d\u4e95\u667a\u4e5f\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u97f3\u58f0\u523a\u6fc0\u4e0b\u306e\u8133\u6d3b\u52d5\u306b\u3088\u308b\u97f3\u58f0\u7279\u5fb4\u91cf\u306e\u63a8\u5b9a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          16. \u5927\u7530\u539f\u83dc\u3005\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u6b05\u60c7\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u8eca\u306e\u5bfe\u8a71\u7684\u64cd\u4f5c\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306e\u81ea\u7136\u8a00\u8a9e\u306e\u7a7a\u9593\u610f\u5473\u8868\u73fe\u306b\u57fa\u3065\u304f\u30b0\u30e9\u30a6\u30f3\u30c6\u30a3\u30f3\u30b0\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          17. \u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4e8b\u524d\u5b66\u7fd2\u30e2\u30c7\u30eb\u3068\u6f5c\u5728\u30c8\u30d4\u30c3\u30af\u3092\u7528\u3044\u305f\u6587\u66f8\u8981\u7d04\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          18. \u5f35\u5609\u7469\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u753b\u50cf\u523a\u6fc0\u6642\u306e\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u3092\u7528\u3044\u305f\u8133\u5185\u60c5\u5831\u89e3\u8aad\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          19. \u6751\u5c71\u53cb\u7406\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u8a18\u61b6\u88c5\u7f6e\u4ed8\u304d\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u30e2\u30c7\u30eb\u306b\u3088\u308b\u6587\u8108\u3068\u69cb\u9020\u5316\u77e5\u8b58\u3092\u7528\u3044\u305f\u5bfe\u8a71\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          20. \u6ff1\u5712\u4f91\u7f8e\uff0c\u4e0a\u539f\u7531\u8863\uff0c\u80fd\u5730\u5b8f\uff0c\u5bae\u5c3e\u7950\u4ecb\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u52d5\u5411\u8aac\u660e\u6587\u751f\u6210\u306b\u304a\u3051\u308b\u53c2\u7167\u6642\u523b\u306e\u4e0d\u6574\u5408\u89e3\u6d88\u306b\u5411\u3051\u305f\u53d6\u308a\u7d44\u307f\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          21. \u5c0f\u6797\u4e00\u90ce.\u300c\u52d5\u4f5c\u3068\u8a00\u8a9e\u306e\u30b7\u30f3\u30dc\u30eb\u30b0\u30e9\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u3078\u306e\u53d6\u308a\u7d44\u307f\uff1a\u81ea\u52d5\u904b\u8ee2\u8eca\u306e\u5bfe\u8a71\u7684\u64cd\u4f5c\u3092\u76ee\u6307\u3057\u3066\u300d. \u7b2c26\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u8328\u57ce\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                          22. <\/i> \u9ed2\u7530\u5f57\u8389\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4e88\u6e2c\u3092\u5bfe\u8c61\u3068\u3059\u308b\u6df1\u5c64\u751f\u6210\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u5b9f\u4e16\u754c\u7406\u89e3\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c82\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u91d1\u6ca2\u5de5\u696d\u5927\u5b66\uff08\u30aa\u30f3\u30e9\u30a4\u30f3\uff09\uff0c2020\u5e743\u6708\uff0eStudent Encouragement Award of IPSJ National Convention<\/a>\u30fbBest Paper Award of IPSJ National Convention<\/a>\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                                                            \n\n\n\n

                                                            2019<\/h2>\n\n\n\n

                                                            <\/i> Journal<\/h3>\n\n\n\n
                                                            1. T. Tangiuchi,D. Mochihashi,T. Nagai,S. Uchida, N. Inoue,I. Kobayashi,T. Nakamura,Y. Hagiwara,N. Iwahashi &T. Inamura, “Survey on frontiers of language and robotics, Journal of Advanced Robotics”. Vol. 33, pp. 700-730, 2019 – Issue 15-16: Special Issue on Robot and Human Interactive Communication (2). <\/i><\/a><\/li>
                                                            2. Masatoshi Nagano, Tomoaki Nakamura, Takayuki Nagai, Daichi Mochihashi, Ichiro Kobayashi, and Wataru Takahashi. “HVGH: Unsupervised Segmentation for High-dimensional Time Series Using Deep Neural Compression and Statistical Generative Model”. Frontiers in Robotics and AI, Computational Intelligence in Robotics, 20th Nov.,2019. <\/i><\/a><\/li>
                                                            3. Akari Inago, Hiroshi Tsukahara, and Ichiro Kobayashi. “Parsing Parking Instructions for Self-driving Cars into Spatial Semantic Descriptions”. Journal of Computers, Vol. 14, pp. 328-338, 2019. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                              <\/i> International Conference<\/h3>\n\n\n\n
                                                              1. Nana Otawara, Hiroshi Tsukahara, Atsushi Keyaki, and Ichiro Kobayashi. “Understanding Natural Language Parking Instructions and Grounding for Self-driving Cars”. Thirty-third Conference on Neural Information Processing Systems, Workshop on Machine Learning for Autonomous Driving, Vancouver, Canada, Dec. 2019. <\/i><\/a><\/li>
                                                              2. Chihiro Fujiyama and Ichiro Kobayashi. “A Comprehensive Analysis of Semantic Compositionality in Text-to-Image Generation”. Thirty-third Conference on Neural Information Processing Systems, Workshop on Visually Grounded Interaction and Language, Vancouver, Canada, Dec. 2019. <\/i><\/a><\/li>
                                                              3. Kasumi Aoki, Akira Miyazawa, Tatsuya Ishigaki, Tatsuya Aoki, Hiroshi Noji, Keiichi Goshima,Ichiro Kobayashi, Hiroya Takamura, Yusuke Miyao. “Controlling Contents in Data-to-Document Generation with Human-Designed Topic Labels”. The International Conference on Natural Language Generation (INLG 2019), Tokyo, Japan, Oct. 2019. <\/i><\/a><\/li>
                                                              4. Kana Ozaki, Satoshi Nishida, Shinji Nishimoto, Hideki Asoh, and Ichiro Kobayashi. “Analysis of Correspondence Relationship between Brain Activity and Semantic Representation”. Cognitive Computational Neuroscience 2019, Berlin, Germany, Sep. 2019. <\/i><\/a><\/li>
                                                              5. Chihiro Fujiyama, Satoshi Nishida, Shinji Nishimoto, Hideki Asoh, and Ichiro Kobayashi. “A Study on a Correlation between a Predictive Model of Motion Pictures Imitating the Predictive Coding of the Cerebral Cortex and Brain Activity”. Cognitive Computational Neuroscience 2019, Berlin, Germany, Sep. 2019. <\/i><\/a><\/li>
                                                              6. Kana Ozaki and Ichiro Kobayashi. “A Study on Stochastic Variational Inference for Topic Modeling with Word Embeddings”. 20th International Conference on Computational Linguistics and Intelligent Text Processing, La Rochelle, France, Apr. 2019. <\/i><\/a><\/li>
                                                              7. Akari Inago, Hiroshi Tsukahara, and Ichiro Kobayashi. “Parsing Parking Instructions for Self-driving Cars into Spatial Semantic Descriptions”. The 8th International Conference on Intelligent Computing and Applications, Melbourne, Australia, Jan. 2019. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                                <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                                                                1. \u6f06\u539f\u7406\u4e43\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u5c71\u53e3\u88d5\u4eba\uff0c\u4e2d\u4e95\u667a\u4e5f\uff0c\u897f\u672c \u4f38\u5fd7.\u300c\u97f3\u58f0\u523a\u6fc0\u306b\u3088\u308b\u8133\u6d3b\u52d5\u306e\u8a00\u8a9e\u89e3\u8aad\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c33\u56de\uff09\uff0c\u6731\u9dfa\u30e1\u30c3\u30bb \uff0c\u65b0\u6f5f\uff0c2019\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                2. \u5927\u7530\u539f\u83dc\u3005\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u306e\u5bfe\u8a71\u7684\u64cd\u4f5c\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306e\u81ea\u7136\u8a00\u8a9e\u306e\u5b9f\u74b0\u5883\u3078\u306e\u30b0\u30e9\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c33\u56de\uff09\uff0c\u6731\u9dfa\u30e1\u30c3\u30bb \uff0c\u65b0\u6f5f\uff0c2019\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                3. \u5f35\u5609\u7469\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u52d5\u753b\u523a\u6fc0\u6642\u306e\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u304b\u3089\u306e\u6587\u751f\u6210\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c33\u56de\uff09\uff0c\u6731\u9dfa\u30e1\u30c3\u30bb \uff0c\u65b0\u6f5f\uff0c2019\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                4. \u6751\u5c71\u53cb\u7406\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u68ee\u7530 \u6b66\u53f2\uff0c\u4e2d\u91ce\u6709\u7d00\u5b50\uff0c\u5c71\u53e3 \u9ad8\u5e73.\u300c\u6587\u8108\u3092\u8003\u616e\u3057\u305f\u5bfe\u8a71\u306e\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u30e2\u30c7\u30eb\u306e\u65e5\u672c\u8a9e\u6ce8\u6587\u5bfe\u8a71\u3078\u306e\u9069\u7528\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c33\u56de\uff09\uff0c\u6731\u9dfa\u30e1\u30c3\u30bb \uff0c\u65b0\u6f5f\uff0c2019\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                5. \u85e4\u5c71\u5343\u7d18, \u5c0f\u6797\u4e00\u90ce.\u300c\u8a00\u8a9e\u304b\u3089\u753b\u50cf\u3092\u751f\u6210\u3059\u308b\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u6319\u52d5\u306b\u95a2\u3059\u308b\u8003\u5bdf\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c33\u56de\uff09\uff0c\u6731\u9dfa\u30e1\u30c3\u30bb \uff0c\u65b0\u6f5f\uff0c2019\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                6. \u4e38\u5343\u5c0b\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6575\u5bfe\u7684\u751f\u6210\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u96c6\u56e3\u578b\u7570\u5e38\u691c\u77e5\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c33\u56de\uff09\uff0c\u6731\u9dfa\u30e1\u30c3\u30bb \uff0c\u65b0\u6f5f\uff0c2019\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                7. \u6f06\u539f\u7406\u4e43\uff0c\u5c71\u53e3\u88d5\u4eba\uff0c\u4e2d\u4e95\u667a\u4e5f\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u97f3\u58f0\u523a\u6fc0\u3092\u7528\u3044\u305f\u8133\u5185\u8a00\u8a9e\u60c5\u5831\u62bd\u51fa\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c35\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5927\u962a\u5927\u5b66\uff0c\u5927\u962a\uff0c2019\u5e748\u6708\uff0e<\/i><\/a><\/li>
                                                                8. \u5c3e\u5d0e\u82b1\u5948\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u9ebb\u751f\u82f1\u6a39\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u53ca\u3073\u610f\u5473\u8868\u8c61\u60c5\u5831\u306e\u5bfe\u5fdc\u95a2\u4fc2\u306e\u8abf\u67fb\u300d. \u7b2c35\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5927\u962a\u5927\u5b66\uff0c\u5927\u962a\uff0c2019\u5e748\u6708\uff0e<\/i><\/a><\/li>
                                                                9. \u6f06\u539f\u7406\u4e43\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u97f3\u58f0\u523a\u6fc0\u4e0b\u306e\u8133\u6d3b\u52d5\u60c5\u5831\u304b\u3089\u306e\u30c6\u30ad\u30b9\u30c8\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c25\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2019\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                10. \u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u5206\u6563\u8868\u73fe\u3092\u7528\u3044\u305f\u30c8\u30d4\u30c3\u30af\u62bd\u51fa\u306b\u304a\u3051\u308b\u78ba\u7387\u7684\u5909\u5206\u63a8\u8ad6\u6cd5\u9069\u7528\u300d. \u7b2c25\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2019\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                11. \u7a32\u5b50\u660e\u91cc\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u904b\u8ee2\u6307\u793a\u6587\u306b\u304a\u3051\u308b\u6642\u7a7a\u9593\u7684\u610f\u5473\u69cb\u9020\u306e\u62bd\u51fa\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c25\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2019\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                12. \u85e4\u5c71\u5343\u7d18\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u753b\u50cf\u3068\u5bfe\u5fdc\u3059\u308b\u8a00\u8a9e\u306e\u610f\u5473\u306e\u5358\u4f4d\u304a\u3088\u3073\u69cb\u6210\u7684\u7279\u6027\u306e\u5206\u6790\u300d. \u7b2c25\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2019\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                13. \u9752\u6728\u82b1\u7d14\uff0c\u5bae\u6fa4\u5f6c\uff0c\u9752\u6728\u7adc\u54c9\uff0c\u80fd\u5730\u5b8f\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u9ad8\u6751\u5927\u4e5f\uff0c\u5bae\u5c3e\u7950\u4ecb.\u300c\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u6982\u8981\u6587\u751f\u6210\u306b\u304a\u3051\u308b\u30c8\u30d4\u30c3\u30af\u30e9\u30d9\u30eb\u306b\u3088\u308b\u5185\u5bb9\u5236\u5fa1\u300d. \u7b2c25\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2019\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                14. <\/i> \u4e38\u5343\u5c0b\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6575\u5bfe\u7684\u751f\u6210\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u7570\u5e38\u691c\u77e5\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c11\u56de\u30c7\u30fc\u30bf\u5de5\u5b66\u3068\u60c5\u5831\u30de\u30cd\u30b8\u30e1\u30f3\u30c8\u306b\u95a2\u3059\u308b\u30d5\u30a9\u30fc\u30e9\u30e0\uff0c\u30cf\u30a6\u30b9\u30c6\u30f3\u30dc\u30b9\uff0c\u9577\u5d0e\uff0c2019\u5e743\u6708\uff0e\u5b66\u751f\u30d7\u30ec\u30bc\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u8cde<\/a>\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                                                                  \n\n\n\n

                                                                  2018<\/h2>\n\n\n\n

                                                                  <\/i> Journal<\/h3>\n\n\n\n
                                                                  1. Kaori Kumagai, Ichiro Kobayashi, Daichi Mochihashi, Hideki Asoh, Tomoaki Nakamura, Takayuki Nagai. \u201dNatural Language Generation Using Monte Carlo Tree Search”. Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.22, No.5, pp.777-785, 2018. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                                    <\/i> International Conference<\/h3>\n\n\n\n
                                                                    1. Yuri Murayama, Ichiro Kobayashi, Takeshi Morita, Yukiko Nakano, Takahira Yamaguchi. “Development of an access method to menu ontology data through converting natural language into SparQL queries”. Workshop and Poster Proceedings of JIST2018, Awaji City, Hyogo, Japan, Nov. 2018. <\/i><\/a><\/li>
                                                                    2. Eri Matsuo, Ichiro Kobayashi, Shinji Nishimoto, Hideki Asoh, and Satoshi Nishida. “Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli”. Special session for BMI H26 (Deciphering Natural Cortical Representations for BMIs), IEEE-SMC 2018, Miyazaki, Japan, Oct. 2018. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                                      <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                                                                      1. \u5927\u7530\u539f\u83dc\u3005\uff0c\u585a\u539f\u88d5\u53f2\uff0c \u5c0f\u6797\u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u306e\u5bfe\u8a71\u7684\u64cd\u4f5c\u3092\u5b9f\u73fe\u3059\u308b\u81ea\u7136\u8a00\u8a9e\u306e\u5b9f\u74b0\u5883\u3078\u306e\u30b0\u30e9\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u300d. \u7b2c36\u56de\u65e5\u672c\u30ed\u30dc\u30c3\u30c8\u5b66\u4f1a\u5b66\u8853\u8b1b\u6f14\u4f1a\uff0c\u4e2d\u90e8\u5927\u5b66\uff0c\u611b\u77e5\uff0c2018\u5e749\u6708\uff0e<\/li>
                                                                      2. \u6a4b\u672c\u3055\u3086\u308a\uff0c\u91d1\u5b50\u6643\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u3092\u7528\u3044\u305f\u8a00\u8449\u306b\u5bfe\u3059\u308b\u52d5\u4f5c\u6982\u5ff5\u7372\u5f97\u3078\u306e\u8a66\u307f\u300d. \u7b2c36\u56de\u65e5\u672c\u30ed\u30dc\u30c3\u30c8\u5b66\u4f1a\u5b66\u8853\u8b1b\u6f14\u4f1a\uff0c\u4e2d\u90e8\u5927\u5b66\uff0c\u611b\u77e5\uff0c2018\u5e749\u6708\uff0e<\/li>
                                                                      3. \u5927\u7530\u539f\u83dc\u3005\uff0c\u585a\u539f\u88d5\u53f2\uff0c \u5c0f\u6797\u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u306e\u5bfe\u8a71\u7684\u64cd\u4f5c\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306e\u81ea\u7136\u8a00\u8a9e\u306e\u7a7a\u9593\u610f\u5473\u8868\u73fe\u306b\u57fa\u3065\u304f\u30b0\u30e9\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30b0\u30e9\u30d5\u306e\u751f\u6210\u300d. \u7b2c34\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2018\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                      4. <\/i> \u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u5206\u6563\u8868\u73fe\u3092\u7528\u3044\u305f\u30c8\u30d4\u30c3\u30af\u62bd\u51fa\u306b\u304a\u3051\u308b\u78ba\u7387\u7684\u5909\u5206\u63a8\u8ad6\u6cd5\u9069\u7528\u3078\u306e\u4e00\u8003\u5bdf\u300d. \u7b2c34\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2018\u5e749\u6708\uff0e\u30dd\u30b9\u30bf\u30fc\u30fb\u30c7\u30e2\u30bb\u30c3\u30b7\u30e7\u30f3\u512a\u79c0\u767a\u8868\u8cde<\/mark>\uff0e<\/i><\/a><\/li>
                                                                      5. \u5f35\u5609\u7469\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u7570\u88ab\u9a13\u8005\u9593\u306e\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u306b\u304a\u3051\u308b\u5bfe\u5fdc\u95a2\u4fc2\u306b\u57fa\u3065\u304f\u985e\u4f3c\u30c7\u30fc\u30bf\u4f5c\u6210\u300d. \u7b2c34\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2018\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                      6. \u6f06\u539f\u7406\u4e43\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4eba\u306e\u52d5\u4f5c\uff0c\u7269\u4f53\u691c\u51fa\u304a\u3088\u3073\u305d\u308c\u3089\u306e\u4f4d\u7f6e\u60c5\u5831\u3092\u8003\u616e\u3057\u305f\u52d5\u753b\u50cf\u304b\u3089\u306e\u6587\u751f\u6210\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      7. \u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u5206\u6563\u8868\u73fe\u3092\u7528\u3044\u305f\u30c8\u30d4\u30c3\u30af\u62bd\u51fa\u306b\u304a\u3051\u308b\u78ba\u7387\u7684\u5909\u5206\u63a8\u8ad6\u6cd5\u9069\u7528\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      8. \u5f35\u5609\u7469\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u7570\u88ab\u9a13\u8005\u9593\u306e\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u76f8\u4e92\u5909\u63db\u306b\u3088\u308b\u64ec\u4f3c\u30c7\u30fc\u30bf\u4f5c\u6210\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      9. \u6751\u5c71\u53cb\u7406\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u68ee\u7530\u6b66\u53f2\uff0c\u4e2d\u91ce\u6709\u7d00\u5b50\uff0c\u5c71\u53e3\u9ad8\u5e73.\u300c\u81ea\u7136\u8a00\u8a9e\u306e SPARQL \u30af\u30a8\u30ea\u5909\u63db\u306b\u57fa\u3065\u304f\u69cb\u9020\u5316\u77e5\u8b58\u3078\u306e\u30a2\u30af\u30bb\u30b9\u624b\u6cd5\u306e\u958b\u767a\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      10. \u7a32\u5b50\u660e\u91cc\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u306e\u99d0\u8eca\u6307\u793a\u3092\u5bfe\u8c61\u306b\u3057\u305f\u7a7a\u9593\u7684\u610f\u5473\u8a18\u8ff0\u306e\u751f\u6210\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      11. \u6a4b\u672c\u3055\u3086\u308a\uff0c\u91d1\u5b50\u6643\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u3068\u8a00\u8449\u306b\u3088\u308b\u96e2\u6563\u5316\u3092\u7528\u3044\u305f\u30ed\u30dc\u30c3\u30c8\u5236\u5fa1\u3078\u306e\u53d6\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      12. \u98ef\u5cf6\u91c7\u6c38\uff0c\u9752\u6728\u82b1\u7d14\uff0c\u5c71\u4e0a\u52dd\u7fa9\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u5c0f\u6fa4\u9806.\u300c\u753b\u50cf\u5165\u529b\u304b\u3089\u63a8\u5b9a\u3059\u308b\u30e6\u30fc\u30b6\u306e\u55dc\u597d\u306b\u57fa\u3065\u304f\u5bfe\u8a71\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      13. \u5ddd\u702c\u5343\u6676\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u8133\u6d3b\u52d5\u3068\u5206\u6563\u8868\u73fe\u306b\u3088\u308b\u610f\u5473\u8868\u8c61\u3078\u306e\u30b9\u30d1\u30fc\u30b9\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u9069\u7528\u306b\u3088\u308a\u7372\u5f97\u3055\u308c\u305f\u8f9e\u66f8\u57fa\u5e95\u306e\u5206\u6790\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c32\u56de\uff09\uff0c\u57ce\u5c71\u30db\u30c6\u30eb\u9e7f\u5150\u5cf6\uff0c\u9e7f\u5150\u5cf6\uff0c2018\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                      14. \u6f06\u539f\u7406\u4e43\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u4eba\u306e\u52d5\u4f5c\u304a\u3088\u3073\u7269\u4f53\u8a8d\u8b58\u306b\u57fa\u3065\u304f\u52d5\u753b\u50cf\u304b\u3089\u306e\u6587\u751f\u6210\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      15. \u5c3e\u5d0e\u82b1\u5948\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u5927\u898f\u6a21\u30c6\u30ad\u30b9\u30c8\u3092\u5bfe\u8c61\u306b\u3057\u305f\u5206\u6563\u8868\u73fe\u306b\u57fa\u3065\u304f\u30c8\u30d4\u30c3\u30af\u62bd\u51fa\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      16. \u5f35\u5609\u7469\uff0c\u677e\u5c3e\u6620\u91cc\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u7570\u88ab\u9a13\u8005\u9593\u306e\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u306b\u304a\u3051\u308b\u76f8\u4e92\u5909\u63db\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      17. \u6751\u5c71\u53cb\u7406\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u68ee\u7530\u6b66\u53f2\uff0c\u4e2d\u91ce\u6709\u7d00\u5b50\uff0c\u5c71\u53e3\u9ad8\u5e73.\u300c\u81ea\u7136\u8a00\u8a9e\u306e SPARQL \u30af\u30a8\u30ea\u5909\u63db\u306b\u57fa\u3065\u304f\u5927\u898f\u6a21\u77e5\u8b58\u3078\u306e\u30a2\u30af\u30bb\u30b9\u624b\u6cd5\u306e\u57fa\u790e\u7684\u691c\u8a0e\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      18. \u7a32\u5b50\u660e\u91cc\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u306e\u305f\u3081\u306e\u99d0\u8eca\u6307\u793a\u304b\u3089\u7a7a\u9593\u610f\u5473\u8a18\u8ff0\u8868\u73fe\u3078\u306e\u5909\u63db\u30d1\u30fc\u30b6\u306e\u7cbe\u5ea6\u5411\u4e0a\u306b\u95a2\u3059\u308b\u53d6\u308a\u7d44\u307f\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      19. \u6a4b\u672c\u3055\u3086\u308a\uff0c\u91d1\u5b50\u6643\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u3092\u7528\u3044\u305f\u30ed\u30dc\u30c3\u30c8\u306e\u81ea\u7136\u8a00\u8a9e\u306b\u3088\u308b\u5236\u5fa1\u3078\u306e\u53d6\u7d44\u307f\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      20. \u98ef\u5cf6\u91c7\u6c38\uff0c\u9752\u6728\u82b1\u7d14\uff0c\u5c71\u4e0a\u52dd\u7fa9\uff0c\u9060\u85e4\u5145\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u5c0f\u6fa4\u9806.\u300c\u753b\u50cf\u5165\u529b\u306b\u3088\u308b\u30ec\u30b7\u30d4\u63d0\u6848\u5bfe\u8a71\u30b7\u30b9\u30c6\u30e0\u306e\u305f\u3081\u306e\u65b9\u7b56\u5b66\u7fd2\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      21. \u67cf\u4e95\u9999\u91cc\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6587\u306e\u985e\u4f3c\u5ea6\u30b0\u30e9\u30d5\u3092\u7528\u3044\u305f\u8907\u6570\u6642\u7cfb\u5217\u6587\u66f8\u8981\u7d04\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      22. \u5ddd\u702c\u5343\u6676\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u304b\u3089\u306e\u30b9\u30d1\u30fc\u30b9\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u306b\u3088\u308b\u610f\u5473\u8868\u8c61\u63a8\u5b9a\u3068\u57fa\u5e95\u306e\u5206\u6790\u300d. \u7b2c24\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a\uff0c\u5ca1\u5c71\u30b3\u30f3\u30d9\u30f3\u30b7\u30e7\u30f3\u30bb\u30f3\u30bf\u30fc\uff0c\u5ca1\u5c71\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li>
                                                                      23. \u5927\u5c71\u307e\u308a\u307b\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u591a\u5c64\u30d1\u30fc\u30bb\u30d7\u30c8\u30ed\u30f3\u3092\u7528\u3044\u305f\u8907\u6570\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u52b9\u7387\u7684\u306a\u5171\u6709\u6f5c\u5728\u7a7a\u9593\u63a8\u5b9a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c80\u56de\u5168\u56fd\u5927\u4f1a\uff0c\u65e9\u7a32\u7530\u5927\u5b66\uff0c\u6771\u4eac\uff0c2018\u5e743\u6708\uff0e<\/i><\/a><\/li><\/ol>\n\n\n\n
                                                                        \n\n\n\n

                                                                        2017<\/h2>\n\n\n\n

                                                                        <\/i> Journal<\/h3>\n\n\n\n
                                                                        1. Ichiro Kobayashi. “An Approach to Meaning: From a Viewpoint of Hallidayan Linguistics”. Cognitive Studies: Bulletin of the Japanese Cognitive Science Society. Vol. 24, Issue. 1, pp. 8-15, 2017. <\/i><\/a><\/li>
                                                                        2. Nakamura Tomoaki, Nagai Takayuki, Mochihashi Daichi, Kobayashi Ichiro, Asoh Hideki, Kaneko Masahide. \u201cSegmenting Continuous Motions with Hidden Semi-Markov Models and Gaussian Pro- cesses\u201d. Frontiers in Neurorobotics, Vol.11, pp.67, 2017. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                                          <\/i> International Conference<\/h3>\n\n\n\n
                                                                          1. Eri Matsuo, Ichiro Kobayashi, Shinji Nishimoto, Hideki Asoh, and Satoshi Nishida. “Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli”. Neural Information Processing 2017 Workshop: Visually-Grounded Interaction and Language (ViGIL), Long Beach, U.S.A., Dec. 2017. <\/i><\/a><\/li>
                                                                          2. Sayuri Hashimoto and Ichiro Kobayashi. “A Basic Study on Action Control Using Deep Reinforcement Learning”. The 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics 2017, Beijing, China, Nov. 2017.<\/li>
                                                                          3. Sae Iijima and Ichiro Kobayashi. “An Approach to Development of a Nursing Care System Using a Multimodal Dialogue System”. The 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics 2017, Beijing, China, Nov. 2017.<\/li>
                                                                          4. Kaori Kashiwai and Ichiro Kobayashi. “Multiple Time-series Documents Summarization based on the Sequential Difference of Events”. The 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics 2017, Beijing, China, Nov. 2017.<\/li>
                                                                          5. Mariho Oyama and Ichiro Kobayashi. “Efficient Estimation for Shared Latent Space Using Multilayer Perceptron”. IEEE-SMC2017, Banff, Canada, Oct. 2017. <\/i><\/a><\/li>
                                                                          6. Chiaki Kawase, Ichiro Kobayashi, Shinji Nishimoto, Hideki Asoh, and Satoshi Nishida. “Semantic Representation in the Cerebral Cortex with Sparse Coding”. IEEE-SMC2017, Banf, Canada, Oct. 2017. <\/i><\/a><\/li><\/ol>\n\n\n\n

                                                                            <\/i> Domestic Conference (in Japanese)<\/h3>\n\n\n\n
                                                                            1. \u7a32\u5b50\u660e\u91cc\uff0c\u585a\u539f\u88d5\u53f2\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u99d0\u8eca\u6307\u793a\u304b\u3089\u7a7a\u9593\u610f\u5473\u8a18\u8ff0\u3078\u306e\u5909\u63db\u30d1\u30fc\u30b6\u306e\u958b\u767a\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                            2. \u6a4b\u672c\u3055\u3086\u308a\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u3092\u7528\u3044\u305f\u4e09\u91cd\u5012\u7acb\u632f\u5b50\u306e\u5236\u5fa1\u306b\u95a2\u3059\u308b\u4e00\u8003\u5bdf\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                            3. <\/i> \u85e4\u5c71\u5343\u7d18\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u5927\u8133\u76ae\u8cea\u306b\u304a\u3051\u308b\u4e88\u6e2c\u7b26\u53f7\u5316\u3092\u6a21\u5023\u3057\u305f\u6df1\u5c64\u52d5\u753b\u50cf\u4e88\u6e2c\u30e2\u30c7\u30eb\u306b\u95a2\u3059\u308b\u8003\u5bdf\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e\u30dd\u30b9\u30bf\u30fc\u30fb\u30c7\u30e2\u30bb\u30c3\u30b7\u30e7\u30f3\u512a\u79c0\u767a\u8868\u8cde<\/mark>\uff0e<\/i><\/a><\/li>
                                                                            4. \u5927\u5c71\u307e\u308a\u307b\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u30ac\u30a6\u30b9\u904e\u7a0b\u306b\u57fa\u3065\u304f\u8907\u6570\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u52b9\u7387\u7684\u306a\u5bfe\u5fdc\u95a2\u4fc2\u5b66\u7fd2\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                            5. \u67cf\u4e95\u9999\u91cc\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u30b0\u30e9\u30d5\u3092\u7528\u3044\u305f\u6642\u7cfb\u5217\u6587\u66f8\u8981\u7d04\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                            6. \u5ddd\u702c\u5343\u6676\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u8133\u6d3b\u52d5\u306e fMRI \u30c7\u30fc\u30bf\u3078\u306e\u758e\u6027\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u9069\u7528\u306b\u3088\u308b\u610f\u5473\u8868\u8c61\u63a8\u5b9a\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e<\/i><\/a><\/li>
                                                                            7. <\/i> \u677e\u5c3e\u6620\u91cc\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u753b\u50cf\u523a\u6fc0\u4e0b\u306e\u8133\u6d3b\u52d5\u5831\u304b\u3089\u306e\u6587\u751f\u6210\u300d. \u7b2c33\u56de\u30d5\u30a1\u30b8\u30a3\u30b7\u30b9\u30c6\u30e0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\uff0c\u5c71\u5f62\u5927\u5b66\uff0c\u5c71\u5f62\uff0c2017\u5e749\u6708\uff0e\u30dd\u30b9\u30bf\u30fc\u30fb\u30c7\u30e2\u30bb\u30c3\u30b7\u30e7\u30f3\u6700\u512a\u79c0\u767a\u8868\u8cde<\/mark>\uff0e<\/i><\/a><\/li>
                                                                            8. \u5927\u5c71\u307e\u308a\u307b\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u591a\u5c64\u30d1\u30fc\u30bb\u30d7\u30c8\u30ed\u30f3\u3092\u7528\u3044\u305f\u52b9\u7387\u7684\u306a\u5171\u6709\u6f5c\u5728\u7a7a\u9593\u306e\u63a8\u5b9a\u300d. ARG\u7b2c10\u56deWeb \u30a4\u30f3\u30c6\u30ea\u30b8\u30a7\u30f3\u30b9\u3068\u30a4\u30f3\u30bf\u30e9\u30af\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a\uff0c\u4eac\u90fd\u5927\u5b66\uff0c\u4eac\u90fd\uff0c2017\u5e747\u6708\uff0e<\/i><\/a><\/li>
                                                                            9. \u7a32\u5b50\u660e\u91cc\uff0c\u585a\u539f \u88d5\u53f2\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u81ea\u52d5\u904b\u8ee2\u306e\u8a00\u8449\u306b\u3088\u308b\u6307\u793a\u3092\u5bfe\u8c61\u306b\u3057\u305f\u7a7a\u9593\u7684\u610f\u5473\u8868\u73fe\u306e\u69cb\u9020\u5316\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                            10. \u6a4b\u672c\u3055\u3086\u308a\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u3092\u7528\u3044\u305f\u52d5\u4f5c\u5236\u5fa1\u3078\u306e\u57fa\u790e\u7684\u691c\u8a0e\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                            11. \u85e4\u5c71\u5343\u7d18\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u5927\u8133\u76ae\u8cea\u306b\u304a\u3051\u308b\u4e88\u6e2c\u7b26\u53f7\u5316\u3092\u6a21\u5023\u3057\u305f\u52d5\u753b\u50cf\u4e88\u6e2c\u30e2\u30c7\u30eb\u3068\u8133\u6d3b\u52d5\u306e\u76f8\u95a2\u306b\u95a2\u3059\u308b\u8003\u5bdf\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                            12. \u98ef\u5cf6\u91c7\u6c38\uff0c\u5c0f\u6797\u4e00\u90ce.\u300c\u30de\u30eb\u30c1\u30e2\u30fc\u30c0\u30eb\u60c5\u5831\u3092\u7528\u3044\u305f\u30ed\u30dc\u30c3\u30c8\u306b\u3088\u308b\u898b\u5b88\u308a\u30b7\u30b9\u30c6\u30e0\u958b\u767a\u306e\u4e00\u8003\u5bdf\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                            13. \u5927\u5c71\u307e\u308a\u307b\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u5171\u6709\u3059\u308b\u6f5c\u5728\u7a7a\u9593\u3092\u7528\u3044\u305f\u7570\u306a\u308b\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u5bfe\u5fdc\u95a2\u4fc2\u5b66\u7fd2\u306b\u95a2\u3059\u308b\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                            14. \u67cf\u4e95\u9999\u91cc\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6587\u66f8\u306e\u6f5c\u5728\u60c5\u5831\u3068\u8868\u5c64\u60c5\u5831\u3092\u8003\u616e\u3057\u305f\u30bf\u30a4\u30e0\u30e9\u30a4\u30f3\u8981\u7d04\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li>
                                                                            15. <\/i> \u5ddd\u702c\u5343\u6676\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u30b9\u30d1\u30fc\u30b9\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u3092\u7528\u3044\u305f\u8133\u6d3b\u52d5\u306e\u610f\u5473\u8868\u8c61\u63a8\u5b9a\u306b\u95a2\u3059\u308b\u7cbe\u5ea6\u5411\u4e0a\u3078\u306e\u53d6\u308a\u7d44\u307f\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0eJSAI Annual Conference Award<\/a>. <\/i><\/a><\/li>
                                                                            16. <\/i> \u677e\u5c3e\u6620\u91cc\uff0c\u5c0f\u6797\u4e00\u90ce\uff0c\u897f\u672c\u4f38\u5fd7\uff0c\u897f\u7530\u77e5\u53f2\uff0c\u9ebb\u751f\u82f1\u6a39.\u300c\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u753b\u50cf\u523a\u6fc0\u6642\u306efMRI\u8133\u6d3b\u52d5\u30c7\u30fc\u30bf\u304b\u3089\u306e\u6587\u751f\u6210\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0eJSAI Annual Conference Award<\/a>. <\/i><\/a><\/li>
                                                                            17. \u9752\u6728\u82b1\u7d14\uff0c\u5c0f\u6797 \u4e00\u90ce.\u300c\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u52d5\u5411\u6982\u8981\u3092\u793a\u3059\u8981\u7d04\u6587\u751f\u6210\u306b\u5411\u3051\u3066\u300d. \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a\uff08\u7b2c31\u56de\uff09\uff0c\u30a6\u30a4\u30f3\u30af\u3042\u3044\u3061\uff0c\u611b\u77e5\uff0c2017\u5e746\u6708\uff0e<\/i><\/a><\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

                                                                              2025 Journal Eri Kuroda and Ichiro Kobayashi. “Predictive Inference Models for Real-world Physical Envir […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":4,"comment_status":"closed","ping_status":"closed","template":"full-width.php","meta":{"_coblocks_attr":"Helvetica,Helvetica","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":""},"_links":{"self":[{"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/pages\/1288"}],"collection":[{"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/comments?post=1288"}],"version-history":[{"count":253,"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/pages\/1288\/revisions"}],"predecessor-version":[{"id":5297,"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/pages\/1288\/revisions\/5297"}],"wp:attachment":[{"href":"https:\/\/www.koba.is.ocha.ac.jp\/kobalab\/index.php\/wp-json\/wp\/v2\/media?parent=1288"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}