| 2025 | AAAI | Synchronization in Learning in Periodic Zero-Sum Games Triggers Divergence from Nash Equilibrium. | Yuma Fujimoto, Kaito Ariu, Kenshi Abe |
| 2025 | AAAI | Approximate State Abstraction for Markov Games. | Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki |
| 2025 | ICLR | Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games. | Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu, Atsushi Iwasaki |
| 2025 | NAACL | Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment. | Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe |
| 2025 | WSDM | Efficient Creative Selection in Online Advertising using Top-Two Thompson Sampling. | Daiki Katsuragawa, Yusuke Kaneko, Kaito Ariu, Kenshi Abe |
| 2024 | AAAI | Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games. | Yuma Fujimoto, Kaito Ariu, Kenshi Abe |
| 2024 | AISTATS | Learning Fair Division from Bandit Feedback. | Hakuei Yamada, Junpei Komiyama, Kenshi Abe, Atsushi Iwasaki |
| 2024 | EMNLP | Filtered Direct Preference Optimization. | Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu |
| 2024 | ICML | Adaptively Perturbed Mirror Descent for Learning in Games. | Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki |
| 2024 | ICML | Model-Based Minimum Bayes Risk Decoding for Text Generation. | Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe |
| 2024 | WWW | Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems. | Riku Togashi, Kenshi Abe, Yuta Saito |
| 2023 | AISTATS | Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games. | Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki |
| 2023 | IJCAI | Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium. | Yuma Fujimoto, Kaito Ariu, Kenshi Abe |
| 2023 | SIGIR | Exploration of Unranked Items in Safe Online Learning to Re-Rank. | Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi |
| 2022 | ICML | Thresholded Lasso Bandit. | Kaito Ariu, Kenshi Abe, Alexandre Proutire |
| 2022 | IJCAI | Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search. | Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki |
| 2022 | UAI | Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games. | Kenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki |