Conference Publications
Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo, Shixiang Shane Gu.
A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation
International Conference on Learning Representations (ICLR 2023) (Notable-top-25%, 8.0% of 4966 submissions).
[arxiv] [code] [website]Hiroki Furuta, Yutaka Matsuo, Shixiang Shane Gu.
Generalized Decision Transformer for Offline Hindsight Information Matching
International Conference on Learning Representations (ICLR 2022) (Spotlight, 6.8% of 3391 submissions).
[arxiv] [code] [website]Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu.
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning
Neural Information Processing Systems (NeurIPS 2021).
[arxiv] [code]Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu.
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
International Conference on Machine Learning (ICML 2021).
[arxiv] [code]Tatsuya Matsushima*, Hiroki Furuta*, Yutaka Matsuo, Ofir Nachum, Shixiang Gu. (*Equal Contribution)
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
International Conference on Learning Representations (ICLR 2021).
[openreview] [code]
Journal Publications
- So Kuroki, Tatsuya Matsushima, Junpei Arima, Hiroki Furuta, Yutaka Matsuo, Shixiang Shane Gu, Yujin Tang.
Collective Intelligence for 2D Push Manipulations With Mobile Robots
IEEE Robotics and Automation Letters (RA-L), 2023.
[paper]
Preprints
Izzeddin Gur*, Hiroki Furuta*, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust. (*Equal Contribution)
A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis
arXiv preprint arXiv:2307.12856, 2023.
[arxiv]Hiroki Furuta, Ofir Nachum, Kuang-Huei Lee, Yutaka Matsuo, Shixiang Shane Gu, Izzeddin Gur.
Multimodal Web Navigation with Instruction-Finetuned Foundation Models
arXiv preprint arXiv:2305.11854, 2023.
[arxiv] [website]Shixiang Shane Gu, Manfred Diaz, C. Daniel Freeman, Hiroki Furuta, Seyed Kamyar Seyed Ghasemipour, Anton Raichuk, Byron David, Erik Frey, Erwin Coumans, Olivier Bachem.
Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Generation Beyond Reward Maximization
arXiv preprint arXiv:2110.04686, 2021.
[arxiv] [code]
Workshop Presentations
Hiroki Furuta, Ofir Nachum, Kuang-Huei Lee, Yutaka Matsuo, Shixiang Shane Gu, Izzeddin Gur.
Instruction-Finetuned Foundation Models for Multimodal Web Navigation
ICLR 2023 Workshop on Multimodal Representation Learning (Spotlight), ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation Models, and ICLR 2023 Workshop on Reincarnating Reinforcement Learning.Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo, Shixiang Shane Gu.
Control Graph as Unified IO for Morphology-Task Generalization
NeurIPS 2022 3rd Offline Reinforcement Learning Workshop: Offline RL as a “Launchpad” (Contributed Talk), and NeurIPS 2022 Foundation Models for Decision Making Workshop.Hiroki Furuta, Yutaka Matsuo, Shixiang Shane Gu.
Generalized Decision Transformer for Offline Hindsight Information Matching
NeurIPS 2021 Deep Reinforcement Learning Workshop.Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu.
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
ICLR 2021 Workshop on Never-Ending RL (Contributed Talk).Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu.
A Unified View of Inference-based Off-Policy RL: Decoupling Algorithmic and Implementational Sources of Performance Differences
NeurIPS 2020 Deep Reinforcement Learning Workshop.Tatsuya Matsushima*, Hiroki Furuta*, Yutaka Matsuo, Ofir Nachum, Shixiang Gu. (*Equal Contribution)
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
NeurIPS 2020 Offline Reinforcement Learning Workshop, and Bay Area Machine Learning Symposium 2020.