| 2026 | AAAI | Beyond Chains: Bridging Large Language Models and Knowledge Bases in Complex Question Answering. | Yihua Zhu, Qianying Liu, Akiko Aizawa, Hidetoshi Shimodaira |
| 2026 | ACL | Establishing a Scale for Kullback-Leibler Divergence in Language Models Across Various Settings. | Ryo Kishino, Yusuke Takase, Momose Oyama, Hiroaki Yamagiwa, Hidetoshi Shimodaira |
| 2026 | ACL | Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs. | Yihua Zhu, Qianying Liu, Jiaxin Wang, Fei Cheng, Chaoran Liu, Akiko Aizawa, Sadao Kurohashi, Hidetoshi Shimodaira |
| 2025 | ACL | Quantifying Lexical Semantic Shift via Unbalanced Optimal Transport. | Ryo Kishino, Hiroaki Yamagiwa, Ryo Nagata, Sho Yokoi, Hidetoshi Shimodaira |
| 2025 | ACL | Mapping 1, 000+ Language Models via the Log-Likelihood Vector. | Momose Oyama, Hiroaki Yamagiwa, Yusuke Takase, Hidetoshi Shimodaira |
| 2025 | COLING | Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings. | Hiroaki Yamagiwa, Momose Oyama, Hidetoshi Shimodaira |
| 2025 | COLING | Norm of Mean Contextualized Embeddings Determines their Variance. | Hiroaki Yamagiwa, Hidetoshi Shimodaira |
| 2025 | EMNLP | Likelihood Variance as Text Importance for Resampling Texts to Map Language Models. | Momose Oyama, Ryo Kishino, Hiroaki Yamagiwa, Hidetoshi Shimodaira |
| 2024 | EACL | 3D Rotation and Translation for Hyperbolic Knowledge Graph Embedding. | Yihua Zhu, Hidetoshi Shimodaira |
| 2024 | EMNLP | Block-Diagonal Orthogonal Relation and Matrix Entity for Knowledge Graph Embedding. | Yihua Zhu, Hidetoshi Shimodaira |
| 2024 | EMNLP | Understanding Higher-Order Correlations Among Semantic Components in Embeddings. | Momose Oyama, Hiroaki Yamagiwa, Hidetoshi Shimodaira |
| 2024 | EMNLP | Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed Embeddings. | Hiroaki Yamagiwa, Yusuke Takase, Hidetoshi Shimodaira |
| 2023 | EMNLP | Norm of Word Embedding Encodes Information Gain. | Momose Oyama, Sho Yokoi, Hidetoshi Shimodaira |
| 2023 | EMNLP | Discovering Universal Geometry in Embeddings with ICA. | Hiroaki Yamagiwa, Momose Oyama, Hidetoshi Shimodaira |
| 2023 | EMNLP | Improving word mover's distance by leveraging self-attention matrix. | Hiroaki Yamagiwa, Sho Yokoi, Hidetoshi Shimodaira |
| 2020 | AISTATS | More Powerful Selective Kernel Tests for Feature Selection. | Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira |
| 2019 | AISTATS | Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability. | Akifumi Okuno, Geewook Kim, Hidetoshi Shimodaira |
| 2019 | AISTATS | Robust Graph Embedding with Noisy Link Weights. | Akifumi Okuno, Hidetoshi Shimodaira |
| 2019 | IJCAI | Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities. | Geewook Kim, Akifumi Okuno, Kazuki Fukui, Hidetoshi Shimodaira |
| 2019 | NAACL | Segmentation-free compositional n-gram embedding. | Geewook Kim, Kazuki Fukui, Hidetoshi Shimodaira |
| 2018 | ICML | A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks. | Akifumi Okuno, Tetsuya Hada, Hidetoshi Shimodaira |
| 2016 | ACL | Cross-Lingual Word Representations via Spectral Graph Embeddings. | Takamasa Oshikiri, Kazuki Fukui, Hidetoshi Shimodaira |
| 2016 | ICIP | Image and tag retrieval by leveraging image-group links with multi-domain graph embedding. | Kazuki Fukui, Akifumi Okuno, Hidetoshi Shimodaira |
| 2010 | ICANN | Assessing Statistical Reliability of LiNGAM via Multiscale Bootstrap. | Yusuke Komatsu, Shohei Shimizu, Hidetoshi Shimodaira |