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    • Could humans be “taken by the wayside” and destroyed by advanced AI? Considering competition and safety in AI development

      山川宏

      ABEMAヒルズ 2024年5月25日

    • Experimental study for a computational model in ITS to predict the learners’ state

      Yoshimasa Tawatsuji

      International Conference on Computers in Education (ICCE 2023). December 2023.

    • Unnatural Error Correction: GPT-4 Can Almost Perfectly Handle Unnatural Scrambled Text

      Qi Cao, Takeshi Kojima, Yutaka Matsuo, Yusuke Iwasawa

      Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023). December 2023.

    • DreamSparse: Escaping from Plato’s Cave with 2D Frozen Diffusion Model given Sparse Views

      Paul Yoo, Jiaxian Guo, Xin Zhang, Yutaka Matsuo, Shixiang Shane Gu

      XRNerf workshop of The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023)

    • Target-Aware Contextual Political Bias Detection in News

      Iffat Maab, Edison Marrese-Taylor, Yutaka Matsuo

      Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL 2023). November 2023

    • AI and Us Artificial Intelligence, Can We Control It?

      山川宏

      朝日新聞デジタル 2023年9月16日

    • Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice

      Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo

      International Conference on Machine Learning (ICML 2023). July 2023.

    • End-to-end Training of Deep Boltzmann Machines by Unbiased Contrastive Divergence with Local Mode Initialization

      Shohei Taniguchi, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo

      International Conference on Machine Learning (ICML 2023) July 2023.

    • BRAES: Developing a Brain Reference Architecture Editorial System for Accumulating Hypotheses on Neural Functionality

      Yoshimasa Tawatsuji, Yuta Ashihara, Naoya Arakawa, Hiroshi Yamakawa

      INCF Neuroinformatics Assembly, 517. September 2023

    • Proposing a Database Extracting Anatomical Structures from Neuroscience Literature and Evaluating Its Information Credibility

      Yuta Ashihara, Hiroshi Yamakawa, Iriya Horiguchi

      INCF Neuroinformatics Assembly, 518.