
Research
Publications
Category
Research Area
Year
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The 23rd Session of the Society of Instrument and Control Engineers, Systems Integration Division (SI2022)Best Presentation Award: Consideration of Data-Driven Service Robot System and its Development Process in WRS2020 Partner Robot Challenge
松嶋達也, 野口裕貴, 有馬純平, 原田憲旺, 青木俊樹, 沖田祐樹, 池田悠也, 石本幸暉, 谷口尚平, 山下優樹, 瀬戸翔一, GU Shixiang Shane, 岩澤有祐, 松尾豊,
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Nov. 2022 Best Poster Award, HSR Community, Research Special Committee on Intelligent Home Robotics, The Robotics Society of Japan
松嶋 達也ほか
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25th Symposium on Image Recognition and Understanding (MIRU2022) MIRU Excellence Award: Pixel vs. Object: A Study on Optimal Image Representation in Change Capture
土居健人, 濱口竜平, 岩澤有祐, 大西正輝, 松尾豊, 櫻田健,
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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.
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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.
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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.
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Computational functions of the brain as seen through anatomical structures
日本神経回路学会誌, Vol.28, No.4
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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.
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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.
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Information-theoretic regularization for learning global features by sequential VAE
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo
Mach Learn (2021)