Yuu Jinnai

Researcher, CyberAgent AI Lab

• Email: ddyuudd [at] gmail [dot] com

Biography

• Jun. 2023- CyberAgent AI Lab.
• Apr. 2020-Jan. 2023 Lily MedTech.
• Summer 2019 I was at MSR Cambridge, UK.
• Jun. 2017-Jul. 2020 Ph.D. student at the Department of Computer Science at Brown University.
• Mar. 2017-May. 2017 Technical staff at RIKEN Center for Advanced Intelligence Project (AIP)
• Mar. 2017 M.A. 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

Research Interests

Artificial Intelligence, Reinforcement Learning, Language Model Alignment, Text Generation, Classical Planning, Heuristic Search

Publications

	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
	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
	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
	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
	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
	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
	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
	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
	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
	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
	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
	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
	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
	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
	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 POSTER CODE
	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
	Jinnai Y, Fukunaga A. 2017. On Hash-Based Work Distribution Methods for Parallel Best-First Search. Journal of Artificial Intelligence Research. (JAIR) PAPER CODE
	(Preprint) Fukunaga A., Botea A, Jinnai Y., Kishimoto A. 2017. A Survey of Parallel A*. arXiv 1708.05296 PAPER
	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
	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

• 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.

• 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.

Seminars

• 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. Thesis Advisor: Alex Fukunaga. University of Tokyo.
  PAPER

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

Others

• 2017 Ichiko Memorial Award (ja), Graduate School of Arts and Sciences, University of Tokyo (2017) (summa cum laude)
• Sep. 2013~Aug. 2016 Resident assistant for international students at Univeristy of Tokyo International lodge, Komaba lodge
• 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 Journal of Machine Learning Research.
• Reviewer of Journal of Artificial Intelligence Research.
• Reviewer of Knowledge-based Systems.