国際会議 / Proceedings
  1. Yamamoto, T., Kumon, R., Bollegala, D., and Yanaka, H., "Neuron-Level Analysis of Cultural Understanding in Large Language Models", 14th International Conference on Learning Representations (ICLR 2026), (2026).
  2. Li, R., and Hitomi, Y., "NeuronMoE: Efficient Cross-Lingual Extension via Neuron-Guided Mixture-of-Experts", Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, (2026).
  3. Yanaka, H., He, X., Jie, L., Han, N., Oh, S., Kumon, R., Matsuoka, Y., Watabe, K., and Itatsu, Y., "Intersectional Bias in Japanese Large Language Models from a Contextualized Perspective", Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP2025) at ACL2025, (2025).
  4. Yanaka, H., Han, N., Kumon, R., Lu, J., Takeshita, M., Sekizawa, R., Katô, T., and Arai, H., "JBBQ: Japanese Bias Benchmark for Analyzing Social Biases in Large Language Models", Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP2025) at ACL2025, (2025).
  5. Yamamoto, T., Kumon, R., Bollegala, D., and Yanaka, H., "Bias Mitigation or Cultural Commonsense? Evaluating LLMs with a Japanese Dataset", Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP2025), 17295–17313, (2025).
  6. Watahiki, A., Doi, T., Shinozaki, T., Nishida, S., Niikawa, T., Miyahara, K., and Yanaka, H., "Bridging Perception and Language: A Systematic Benchmark for LVLMs’ Understanding of Amodal Completion Reports", Proceedings of the 47th Annual Conference of the Cognitive Science Society (CogSci2025), (2025).
  7. Tomita, A., Yanaka, H., and Bekki, D., "Automatic Evaluation of Linguistic Validity in Japanese CCG Treebanks", Proceedings of the 23rd Workshop on Treebanks and Linguistic Theories, (2025).
  8. Takagi, H., Minegishi, G., Kizawa, S., Sukeda, I., and Yanaka, H., "Interpreting Multi-Attribute Confounding through Numerical Attributes in Large Language Models", Proceedings of International Joint Conference on Natural Language Processing & Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL2025), (2025).
  9. Shinozaki, T., Doi, T., Watahiki, A., Nishida, S., and Yanaka, H., "Do Large Vision-Language Models Distinguish between the Actual and Apparent Features of Illusions?", Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL2025), (2025).
  10. Ryu, K., and Yanaka, H., "Enhancing Rating Prediction with Off-the-Shelf LLMs Using In-Context User Reviews", Enhancing Rating Prediction with Off-the-Shelf LLMs Using In-Context User Reviews, (2025).
  11. Mikami, Y., Matsuoka, D., and Yanaka, H., "Implementing a Logical Inference System for Japanese Comparatives", Proceedings of the 5th Workshop on Natural Logic Meets Machine Learning (NALOMA), (2025).
  12. Mikami, Y., Matsuoka, D., and Yanaka, H., "Can Large Language Models Robustly Perform Natural Language Inference for Japanese Comparatives?", Proceedings of the 16th International Conference on Computational Semantics (IWCS2025), (2025).
  13. Lu, J., Jin, D., and Yanaka, H., "LLMs Struggle with NLI for Perfect Aspect: A Cross-Linguistic Study in Chinese and Japanese", Proceedings of the 16th International Conference on Computational Semantics (IWCS2025), (2025).
  14. Kumon, R., and Yanaka, H., "Analyzing the Inner Workings of Transformer in Compositional Generalization", Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL2025), (2025).