Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search. - Yuu Jinnai; Alex Fukunaga (AAAI, 2016)

Automated Creation of Efficient Work Distribution Functions for Parallel Best-First Search. - Yuu Jinnai; Alex S. Fukunaga (ICAPS, 2016)

Learning to Prune Dominated Action Sequences in Online Black-Box Planning. - Yuu Jinnai; Alex S. Fukunaga (AAAI, 2017)

Learning to Avoid Dominated Action Sequences in Planning for Black-Box Domains. - Yuu Jinnai; Alex Fukunaga (AAAI, 2017)

A Survey of Parallel A. - Alex Fukunaga; Adi Botea; Yuu Jinnai; Akihiro Kishimoto (CoRR, 2017)

On Hash-Based Work Distribution Methods for Parallel Best-First Search. - Yuu Jinnai; Alex Fukunaga (J. Artif. Intell. Res., 2017)

Parallel A* for State-Space Search. - Alex Fukunaga; Adi Botea; Yuu Jinnai; Akihiro Kishimoto (Handbook of Parallel Constraint Reasoning, 2018)

Policy and Value Transfer in Lifelong Reinforcement Learning. - David Abel; Yuu Jinnai; Yue (Sophie) Guo; George Dimitri Konidaris; Michael L. Littman (ICML, 2018)

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. - Linnan Wang; Yiyang Zhao; Yuu Jinnai (CoRR, 2018)

Finding Options that Minimize Planning Time. - Yuu Jinnai; David Abel; Michael L. Littman; George Dimitri Konidaris (CoRR, 2018)

State Abstraction as Compression in Apprenticeship Learning. - David Abel; Dilip Arumugam; Kavosh Asadi; Yuu Jinnai; Michael L. Littman; Lawson L. S. Wong (AAAI, 2019)

Finding Options that Minimize Planning Time. - Yuu Jinnai; David Abel; David Ellis Hershkowitz; Michael L. Littman; George Dimitri Konidaris (ICML, 2019)

Discovering Options for Exploration by Minimizing Cover Time. - Yuu Jinnai; Jee Won Park; David Abel; George Dimitri Konidaris (ICML, 2019)

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. - Linnan Wang; Yiyang Zhao; Yuu Jinnai; Yuandong Tian; Rodrigo Fonseca (CoRR, 2019)

Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search. - Linnan Wang; Yiyang Zhao; Yuu Jinnai; Yuandong Tian; Rodrigo Fonseca (AAAI, 2020)

Exploration in Reinforcement Learning with Deep Covering Options. - Yuu Jinnai; Jee Won Park; Marlos C. Machado; George Dimitri Konidaris (ICLR, 2020)

Lipschitz Lifelong Reinforcement Learning. - Erwan Lecarpentier; David Abel; Kavosh Asadi; Yuu Jinnai; Emmanuel Rachelson; Michael L. Littman (AAAI, 2021)

Blind Signal Separation for Fast Ultrasound Computed Tomography. - Takumi Noda; Yuu Jinnai; Naoki Tomii; Takashi Azuma (CoRR, 2023)

On the Depth between Beam Search and Exhaustive Search for Text Generation. - Yuu Jinnai; Tetsuro Morimura; Ukyo Honda (CoRR, 2023)

Model-Based Minimum Bayes Risk Decoding. - Yuu Jinnai; Tetsuro Morimura; Ukyo Honda; Kaito Ariu; Kenshi Abe (CoRR, 2023)

Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding. - Yuu Jinnai; Kaito Ariu (ACL (Findings), 2024)

Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding. - Yuu Jinnai; Ukyo Honda; Tetsuro Morimura; Peinan Zhang (ACL (Findings), 2024)

Filtered Direct Preference Optimization. - Tetsuro Morimura; Mitsuki Sakamoto; Yuu Jinnai; Kenshi Abe; Kaito Ariu (EMNLP, 2024)

Model-Based Minimum Bayes Risk Decoding for Text Generation. - Yuu Jinnai; Tetsuro Morimura; Ukyo Honda; Kaito Ariu; Kenshi Abe (ICML, 2024)

On the True Distribution Approximation of Minimum Bayes-Risk Decoding. - Atsumoto Ohashi; Ukyo Honda; Tetsuro Morimura; Yuu Jinnai (NAACL (Short Papers), 2024)

Regularized Best-of-N Sampling to Mitigate Reward Hacking for Language Model Alignment. - Yuu Jinnai; Tetsuro Morimura; Kaito Ariu; Kenshi Abe (CoRR, 2024)

Annotation-Efficient Preference Optimization for Language Model Alignment. - Yuu Jinnai; Ukyo Honda (CoRR, 2024)

Does Cross-Cultural Alignment Change the Commonsense Morality of Language Models? - Yuu Jinnai (CoRR, 2024)

Theoretical Guarantees for Minimum Bayes Risk Decoding. - Yuki Ichihara; Yuu Jinnai; Kaito Ariu; Tetsuro Morimura; Eiji Uchibe (ACL (1), 2025)

Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport. - Yuu Jinnai (ACL (1), 2025)

Do Large Language Models Know Folktales? A Case Study of Yokai in Japanese Folktales. - Ayuto Tsutsumi; Yuu Jinnai (ACL (Findings), 2025)

Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment. - Yuu Jinnai; Tetsuro Morimura; Kaito Ariu; Kenshi Abe (NAACL (Long Papers), 2025)

Evaluation of Best-of-N Sampling Strategies for Language Model Alignment. - Yuki Ichihara; Yuu Jinnai; Tetsuro Morimura; Kenshi Abe; Kaito Ariu; Mitsuki Sakamoto; Eiji Uchibe (Trans. Mach. Learn. Res., 2025)

MO-GRPO: Mitigating Reward Hacking of Group Relative Policy Optimization on Multi-Objective Problems. - Yuki Ichihara; Yuu Jinnai; Tetsuro Morimura; Mitsuki Sakamoto; Ryota Mitsuhashi; Eiji Uchibe (CoRR, 2025)

Re-evaluating Minimum Bayes Risk Decoding for Automatic Speech Recognition. - Yuu Jinnai (CoRR, 2025)