| 2025 | ACL | Theoretical Guarantees for Minimum Bayes Risk Decoding. | Yuki Ichihara, Yuu Jinnai, Kaito Ariu, Tetsuro Morimura, Eiji Uchibe |
| 2025 | ACL | Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport. | Yuu Jinnai |
| 2025 | ACL | Do Large Language Models Know Folktales? A Case Study of Yokai in Japanese Folktales. | Ayuto Tsutsumi, Yuu Jinnai |
| 2025 | EMNLP | Auto-Weighted Group Relative Preference Optimization for Multi-Objective Text Generation Tasks. | Yuki Ichihara, Yuu Jinnai |
| 2025 | EMNLP | Annotation-Efficient Language Model Alignment via Diverse and Representative Response Texts. | Yuu Jinnai, Ukyo Honda |
| 2025 | NAACL | Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment. | Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe |
| 2024 | ACL | Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding. | Yuu Jinnai, Kaito Ariu |
| 2024 | ACL | Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding. | Yuu Jinnai, Ukyo Honda, Tetsuro Morimura, Peinan Zhang |
| 2024 | EMNLP | Filtered Direct Preference Optimization. | Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu |
| 2024 | ICML | Model-Based Minimum Bayes Risk Decoding for Text Generation. | Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe |
| 2024 | NAACL | On the True Distribution Approximation of Minimum Bayes-Risk Decoding. | Atsumoto Ohashi, Ukyo Honda, Tetsuro Morimura, Yuu Jinnai |
| 2021 | AAAI | Lipschitz Lifelong Reinforcement Learning. | Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman |
| 2020 | AAAI | Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search. | Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca |
| 2020 | ICLR | Exploration in Reinforcement Learning with Deep Covering Options. | Yuu Jinnai, Jee Won Park, Marlos C. Machado, George Dimitri Konidaris |
| 2019 | AAAI | State Abstraction as Compression in Apprenticeship Learning. | David Abel, Dilip Arumugam, Kavosh Asadi, Yuu Jinnai, Michael L. Littman, Lawson L. S. Wong |
| 2019 | ICML | Finding Options that Minimize Planning Time. | Yuu Jinnai, David Abel, David Ellis Hershkowitz, Michael L. Littman, George Dimitri Konidaris |
| 2019 | ICML | Discovering Options for Exploration by Minimizing Cover Time. | Yuu Jinnai, Jee Won Park, David Abel, George Dimitri Konidaris |
| 2018 | ICML | Policy and Value Transfer in Lifelong Reinforcement Learning. | David Abel, Yuu Jinnai, Yue (Sophie) Guo, George Dimitri Konidaris, Michael L. Littman |
| 2017 | AAAI | Learning to Prune Dominated Action Sequences in Online Black-Box Planning. | Yuu Jinnai, Alex S. Fukunaga |
| 2017 | AAAI | Learning to Avoid Dominated Action Sequences in Planning for Black-Box Domains. | Yuu Jinnai, Alex Fukunaga |
| 2016 | AAAI | Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search. | Yuu Jinnai, Alex Fukunaga |