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Yuu Jinnai
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Project: Parallel Best-First Search
Project: Automated Skill Discovery
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Japanese: Open Data Structures
Japanese: ヒューリスティック探索入門
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Yuu Jinnai

Researcher, CyberAgent AI Lab
- Email: ddyuudd [at] gmail [dot] com
Biography
- Jun. 2023- Researcher, CyberAgent AI Lab.
- Apr. 2020-Jan. 2023 Engineer, Lily MedTech Inc.
- Summer 2019 Intern, MSR Cambridge, UK.
- Jun. 2017-Jan. 2020 (Incomplete) Ph.D. student, the Department of Computer Science at Brown University. Advised by George Konidaris.
- Mar. 2017-May. 2017 Technical staff, RIKEN Center for Advanced Intelligence Project (AIP).
- Mar. 2017 M.A. degree from Graduate School of Arts and Sciences, the University of Tokyo. Advised by Alex Fukunaga.
- Mar. 2015 B.S. degree from the University of Tokyo. Advised by Alex Fukunaga.
Research Interests
Artificial Intelligence, Reinforcement Learning, Language Model Alignment, Text Generation, Classical Planning, Heuristic Search
Publications
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Yuu Jinnai and Ukyo Honda. 2025. Annotation-Efficient Preference Optimization for Language Model Alignment. In Findings of the Association for Computational Linguistics (EMNLP-25 Findings). PAPER CODE TALK |
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Yuki Ichihara, Yuu Jinnai, Kaito Ariu, Tetsuro Morimura, Eiji Uchibe. 2025. Theoretical Guarantees for Minimum Bayes Risk Decoding. Annual Meeting of the Association for Computational Linguistics (ACL-25). PAPER |
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Ayuto Tsutsumi, Yuu Jinnai. 2025. Do Large Language Models Know Folktales? A Case Study of Yokai in Japanese Folktales. In Findings of the Association for Computational Linguistics (ACL-25 Findings). PAPER CODE DATASET |
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Yuu Jinnai. 2025. Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport. Annual Meeting of the Association for Computational Linguistics (ACL-25). PAPER CODE TALK TALK |
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Ichihara, Y., Jinnai, Y., Morimura, T., Ariu, K., Abe, K., Sakamoto, M., & Uchibe, E. (2025). Evaluation of Best-of-N Sampling Strategies for Language Model Alignment. Transactions on Machine Learning Research (TMLR) PAPER CODE TALK |
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Jinnai, Y., Morimura, T., Ariu, K., & Abe, K. (2024). Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment. 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL-25) PAPER CODE TALK |
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Morimura, T., Sakamoto, M., Jinnai, Y., Abe, K., & Ariu, K. (2024). Filtered Direct Preference Optimization. The 2024 Conference on Empirical Methods in Natural Language Processing. (EMNLP-24) PAPER CODE |
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Jinnai Y. 2024. Does Cross-Cultural Alignment Change the Commonsense Morality of Language Models? Proceedings of the 2nd Workshop on Cross-Cultural Considerations in NLP (C3NLP Workshop at ACL 2024). Best Paper Award. PAPER TALK MODEL DATASET |
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Jinnai Y, Morimura T, Honda U, Ariu K, Abe K. Model-based minimum bayes risk decoding. Proc. 41st International Conference on Machine Learning. (ICML-24) PAPER CODE TALK |
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Jinnai Y, Ariu K. Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding. In Findings of the Association for Computational Linguistics. (ACL-24 Findings) PAPER CODE TALK |
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Jinnai Y, Honda U, Morimura T, Zhang P. Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding. In Findings of the Association for Computational Linguistics. (ACL-24 Findings) PAPER CODE TALK |
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Ohashi A, Honda U, Morimura T, Jinnai Y. 2024. On the True Distribution Approximation of Minimum Bayes-Risk Decoding. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL-24) PAPER CODE TALK |
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Lecarpentier E, Abel D, Asadi K, Jinnai Y, Rachelson E, Littman Michael L. 2021. Lipschitz Lifelong Reinforcement Learning. Proc. 35th AAAI conference on Artificial Intelligence (AAAI-21) arXiv Poster CODE |
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Y. Jinnai, J. Park, M.C. Machado, and G.D. Konidaris. Exploration in Reinforcement Learning with Deep Covering Options. Accepted, Proceedings of the Eighth International Conference on Learning Representations. (ICLR-20) PAPER |
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Wang L*, Zhao Y*, Jinnai Y, Tian Y, Fonseca R. 2020. AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. Proc. 34th AAAI conference on Artificial Intelligence (AAAI-20) *These authors contributed equally to this work. PAPER CODE |
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Jinnai Y. Park JW, Abel D, Konidaris G. 2019. Discovering Options for Exploration by Minimizing Cover Time. Proc. 36th International Conference on Machine Learning. (ICML-19) PAPER CODE TALK |
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Jinnai Y, Abel D, Hershkowitz E, Littman M, Konidaris G. 2019. Finding Options that Minimize Planning Time. Proc. 36th International Conference on Machine Learning. (ICML-19) PAPER CODE TALK |
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Jinnai Y, Abel D, Park JW, Hershkowitz E, Littman M, Konidaris G. 2019. Skill Discovery with Well-Defined Objectives. ICLR Worshop on Structure and Priors in Reinforcement Learning. PAPER |
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Abel D, Arumugam D, Asadi K, Jinnai Y, Littman M, Wong L. S. 2019. State Abstraction as Compression in Apprenticeship Learning. Proc. 33rd AAAI Conference on Artificial Intelligence (AAAI-19). PAPER CODE |
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Abel D*, Jinnai Y*, Guo Y, Konidaris G, Littman M. 2018. Policy and Value Transfer for Lifelong Reinforcement Learning. Proc. 35th International Conference on Machine Learning. (ICML-18) *These authors contributed equally to this work. PAPER POSTER CODE TALK by D. Abel |
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Fukunaga A, Botea A, Jinnai Y, Kishimoto A. 2018. Parallel A* for State-Space Search. Handbook of Parallel Constraint Reasoning, Youssef Hamadi, Lakhdar Sais (eds.), Springer. ISBN 978-3-319-63515-6. BOOK |
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Jinnai Y, Fukunaga A. 2017. A Graph-Partitioning Based Approach for Parallel Best-First Search. ICAPS 2017 Workshop on Heuristic and Search for Domain-Independent Planning (HSDIP). PAPER SLIDES CODE |
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Jinnai Y, Fukunaga A. 2017. Learning to Prune Dominated Action Sequences in Online Black-box Planning. Proc. 31st AAAI Conference on Artificial Intelligence. (AAAI-17) PAPER SLIDES CODE |
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Jinnai Y, Fukunaga A. 2017. On Hash-Based Work Distribution Methods for Parallel Best-First Search. Journal of Artificial Intelligence Research. (JAIR) PAPER CODE |
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(Preprint) Fukunaga A., Botea A, Jinnai Y., Kishimoto A. 2017. A Survey of Parallel A*. arXiv 1708.05296 PAPER |
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Jinnai Y, Fukunaga A. 2016. Automated Creation of Efficient Work Distribution Functions for Parallel Best-First Search. Proc. 19th International Conference on Automated Planning and Scheduling. (ICAPS-16) PAPER SLIDES VIDEO CODE |
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Jinnai Y, Fukunaga A. 2016. Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search. Proc. 30th AAAI Conference on Artificial Intelligence. (AAAI-16) PAPER POSTER CODE (PDDL) CODE (sliding-tile, path-finding, MSA) |
Grants/Scholarships
- 2015-2017 JASSO scholarship with particularly outstanding academic achievements (approx. $21,000)
- 2017 Department of System Sciences: Grants for Doctoral Students Attending International Conferences (ja) (AAAI-17)
- 2016 Initiative on Promotion of Supercomputing for Young or Women Researchers,Supercomputing Division,Information Technology Center,The University of Tokyo
- 2016 NEC C&C Foundation: Grants for Researchers Attending International Conferences (ICAPS-16)
- 2016 Department of System Sciences: Grants for Doctoral Students Attending International Conferences (ja) (AAAI-16)
Teaching
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2016 Winter Semester (University of Tokyo)
Teaching assistant for Terakoya program, which is a program to walk through introductory level math and computer science for undergraduates at the University of Tokyo. -
2016 Summer Semester (University of Tokyo)
I was working as a teaching assistant (TA) for information engineering at the University of Tokyo. -
2015 Summer (Tama High School of Science and Technology) I was working as a part-time instructor at Tama High School of Science and Technology to teach scientific presentation.
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2015 Winter Semester (University of Tokyo)
I was teaching introductory graph theory with flip-teaching style for Terakoya program at the University of Tokyo. -
2015 Summer Semester (University of Tokyo)
I was a teaching assistant (TA) for first year seminar for science student at the University of Tokyo. I was a teaching assistant (TA) for information engineering at the University of Tokyo.
Patents
- Medical information provision device, ultrasonic ct imaging device, and medical information provision system Google Patents
- Tumor detection algorithm for ultrasound computed tomography Google Patents
- Spiculated mass detection algorithm for ultrasound computed tomography Google Patents
- Motion artifact detection for ultrasound computed tomography Google Patents
- Faster ultrasound computed tomography by ultrasound signal separation Google Patents
Seminars
- Jun. 2025. Introduction to Minimum Bayes Risk Decoding. NLP Colloquium.
SLIDES - Jan. 2018. Automated Deep Learning by Neural Architecture Search. National Institute of Information and Communications Technology, Japan.
- Feb. 2017. Graph search algorithms for classical planning. Discrete Structure Manipulation System Project. Hokkaido University, Japan.
Thesis
- Master Thesis
Jinnai Y. 2017. On Hash-Based Work Distribution Methods for Parallel Best-First Search. Advisor: Alex Fukunaga. University of Tokyo.
PAPER
Awards and honors
- Best Paper Award. 2024. Jinnai Y. Does Cross-Cultural Alignment Change the Commonsense Morality of Language Models? Proceedings of the 2nd Workshop on Cross-Cultural Considerations in NLP (C3NLP Workshop at ACL 2024)
- Graduated summa cum laude. 2017. Ichiko Memorial Award, Graduate School of Arts and Sciences, University of Tokyo.
Services
- Reviewer of International Conference of Machine Learning (ICML), Neural Information Processing Systems (NeurIPS), AAAI Conference on Artificial Intelligence (AAAI), International Conference on Learning Representations (ICLR).
- Reviewer of ACL (Association for Computational Linguistics) Rolling Review.
- Reviewer of Journal of Machine Learning Research.
- Reviewer of Journal of Artificial Intelligence Research.
- Reviewer of Knowledge-based Systems.
- Program Committee of 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP).
- Program Committee of UncertaiNLP: 2nd Workshop on Uncertainty-Aware NLP.


























