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    • 受賞
      LLM / NLP コンピュータービジョン

      第25回画像の認識・理解シンポジウム (MIRU2022) MIRU優秀賞: Pixel vs. Object: 変化キャプショニングにおける最適な画像表現についての研究

      土居健人, 濱口竜平, 岩澤有祐, 大西正輝, 松尾豊, 櫻田健,

    • 受賞
      LLM / NLP

      Best Paper Award：“On the Impact of Data Augmentation on Downstream Performance in Natural Language Processing”. Proceedings of the Third Workshop on Insights from Negative Results in NLP, Online and Dublin, Ireland. Association for Computational Linguistics, 2022

      Itsuki Okimura, Machel Reid, Makoto Kawano and Yutaka Matsuo.

    • 国際会議
      世界モデル

      Improving the Robustness to Variations of Objects and Instructions with a Neuro-Symbolic Approach for Interactive Instruction Following

      Kazutoshi Shinoda, Yuki Takezawa, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo

      Workshop on Novel Ideas in Learning-to-Learn through Interaction, EMNLP 2021.

    • 国際会議
      コンピュータービジョン 理論 表現学習

      Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization

      Yusuke Iwasawa, and Yutaka Matsuo.

      Advances in Neural Information Processing Systems 2021 (NeurIPS2021, Spotlight). December 2021.

    • 国際会議
      強化学習 理論 表現学習

      Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning

      Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, and Shixiang Shane Gu.

      Advances in Neural Information Processing Systems 2021 (NeurIPS2021). December 2021.

    • 記事・出演
      Brain-Inspired Intelligence

      解剖学的構造から見える脳の計算機能

      日本神経回路学会誌, Vol.28, No.4

    • 国内会議
      Brain-Inspired Intelligence

      上位オントロジーの主要概念の捉え方の整理

      田和辻可昌, 荒川直哉, 山川宏

      人工知能学会SWO研究会

    • 国際会議
      LLM / NLP

      AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages

      Machel Reid, Junjie Hu, Graham Neubig and Yutaka Matsuo

      The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021). November 2021. Association for Computational Linguistics.

    • 国際会議
      LLM / NLP

      Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

      Machel Reid, Edison Marrese-Taylor and Yutaka Matsuo.

      Findings of The 2021 Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP 2021). Association for Computational Linguistics. 

    • 論文誌
      理論 表現学習

      “Information-theoretic regularization for learning global features by sequential VAE”

      Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo

      Mach Learn (2021)