Publications

1. Minimally Invasive Morphology Adaptation via Parameter Efficient Fine-Tuning Michael Przystupa, Hongyao Tang, Mariano Phielipp, Santiago Miret, Martin Jägersand, and \textbfBerseth In [CoRL 2024] Morphology-Aware Policy and Design Learning Workshop (MAPoDeL) [Link]

2. RLeXplore: Accelerating Research in Intrinsically-Motivated Reinforcement Learning Mingqi Yuan, Roger Creus Castanyer, Bo Li, Xin Jin, Glen Berseth, and Wenjun Zeng [Link]

3. Adaptive Resolution Residual Networks Léa Demeule, Mahtab Sandhu, and Glen Berseth The Symbiosis of Deep Learning and Differential Equations III - a NeurIPS2023 workshop (Oral) [Link]

4. Inter-Level Cooperation in Hierarchical Reinforcement Learning Abdul Rahman Kreidieh, Glen Berseth, Brandon Traboco Samyak Parajuli, Sergey Levine, and Alexandre M. Bayen Under submission to Journal of Machine Learning Research arXiv |

1. Enhancing Agent Learning through World Dynamics Modeling Zhiyuan Sun, Haochen Shi, Marc-Alexandre Côté, Glen Berseth, Xingdi Yuan, and Bang Liu In The 2024 Conference on Empirical Methods in Natural Language Processing [Link]

2. Amortizing intractable inference in diffusion models for vision, language, and control Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, and Nikolay Malkin In Advances in Neural Information Processing Systems [Link]

3. Open X-Embodiment: Robotic Learning Datasets and RT-X Models (ICRA2024 best paper) Open X-Embodiment Collaboration, Abby O’Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Hao-Shu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi "Jim" Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J Joshi, Niko Suenderhauf, Ning Liu, Norman Di Palo, Nur Muhammad Mahi Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R Sanketi, Patrick "Tree" Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Mart’in-Mart’in, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Xu Liangwei, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, and Zipeng Lin International Conference on Robotics and Automation (ICRA 2024) [Link] Project Page | Code |

4. Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn Hongyao Tang, and \textbfGlen \textbfBerseth In Advances in Neural Information Processing Systems [Link]

5. Simplifying Constraint Inference with Inverse Reinforcement Learning Adriana Hugessen, Harley Wiltzer, and \textbfGlen \textbfBerseth In Advances in Neural Information Processing Systems [Link]

6. DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, Jensen Gao, David Antonio Herrera, Minho Heo, Kyle Hsu, Jiaheng Hu, Donovon Jackson, Charlotte Le, Yunshuang Li, Kevin Lin, Roy Lin, Zehan Ma, Abhiram Maddukuri, Suvir Mirchandani, Daniel Morton, Tony Nguyen, Abigail O’Neill, Rosario Scalise, Derick Seale, Victor Son, Stephen Tian, Emi Tran, Andrew E. Wang, Yilin Wu, Annie Xie, Jingyun Yang, Patrick Yin, Yunchu Zhang, Osbert Bastani, Glen Berseth, Jeannette Bohg, Ken Goldberg, Abhinav Gupta, Abhishek Gupta, Dinesh Jayaraman, Joseph J Lim, Jitendra Malik, Roberto Martín-Martín, Subramanian Ramamoorthy, Dorsa Sadigh, Shuran Song, Jiajun Wu, Michael C. Yip, Yuke Zhu, Thomas Kollar, Sergey Levine, and Chelsea Finn In Robotics: Science and Systems XX, 2024 [Link] Project Page | Video |

7. Surprise-Adaptive Intrinsic Motivation for Unsupervised Reinforcement Learning Adriana Knatchbull-Hugessen, Roger Creus-Castanyer, Faisal Mohamed, and Glen Berseth Reinforcement Learning Conference 2024 [Link]

8. Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, and Koushil Sreenath International Journal of Robotics Research arXiv | Video |

9. Improving Intrinsic Exploration by Creating Stationary Objectives Roger Creus Castanyer, Joshua Romoff, and Glen Berseth In The Twelfth International Conference on Learning Representations arXiv | [Link]

10. Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View Raj Ghugare, Matthieu Geist, Benjamin Eysenbach, and Glen Berseth In The Twelfth International Conference on Learning Representations arXiv | [Link]

11. Intelligent Switching for Reset-Free RL Darshan Patil, Janarthanan Rajendran, Glen Berseth, and Sarath Chandar In The Twelfth International Conference on Learning Representations [Link]

12. Searching the space of high-value molecules using reinforcement learning and language models Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, and Glen Berseth In The Twelfth International Conference on Learning Representations arXiv | [Link] Project Page |

13. Reasoning with Latent Diffusion in Offline Reinforcement Learning Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John Dolan, Jeff Schneider, and Glen Berseth In The Twelfth International Conference on Learning Representations arXiv | [Link]

1. Maximum State Entropy Exploration using Predecessor and Successor Representations Arnav Kumar Jain, Lucas Lehnert, Irina Rish, and Glen Berseth In Thirty-seventh Conference on Neural Information Processing Systems arXiv | [Link]

2. Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, and Sergey Levine In Proc. IEEE/RSJ Intl Conf on Intelligent Robots and Systems (IROS 2023) arXiv | [Link] Project Page |

3. Torque-based Deep Reinforcement Learning for Task-and-Robot Agnostic Learning on Bipedal Robots Using Sim-to-Real Transfer Donghyeon Kim, Glen Berseth, Mathew Schwartz, and Jaeheung Park IEEE Robotics and Automation Letters arXiv | Video |

4. Robust and Versatile Bipedal Jumping Control through Reinforcement Learning Zhongyu Li, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, and Koushil Sreenath In Robotics: Science and Systems XIX, Daegu, Republic of Korea, July 10-14, 2023 arXiv | [Link] Video |

5. Towards Learning to Imitate from a Single Video Demonstration Glen Berseth, Florian Golemo, and Christopher Pal J. Mach. Learn. Res. [HTML] [Link] Project Page | Video |

1. Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot Yandong Ji, Zhongyu Li*, Yinan Sun, Xue Bin Peng, Sergey Levine, Glen Berseth, and Koushil Sreenath In Proc. IEEE/RSJ Intl Conf on Intelligent Robots and Systems (IROS 2022) arXiv | Video |

2. AnyMorph: Learning Transferable Policies By Inferring Agent Morphology Brandon Trabucco, Phielipp Mariano, and Glen Berseth Internation Conference on Machine Learning arXiv | Project Page |

3. ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning Sean Chen*, Jensen Gao*, Siddharth Reddy, Glen Berseth, Anca D. Dragan, and Sergey Levine IEEE International Conference on Robotics and Automation (ICRA) arXiv | [Link] Project Page | Code | Video |

4. CoMPS: Continual Meta Policy Search Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, and Sergey Levine In International Conference on Learning Representations arXiv | [Link] Project Page | Video |

1. Explore and Control with Adversarial Surprise Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, and Sergey Levine CoRR arXiv | [Link] Project Page | Video |

2. Information is Power: Intrinsic Control via Information Capture Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D Co-Reyes, Danijar Hafner, Chelsea Finn, and Sergey Levine In Advances in Neural Information Processing Systems arXiv | [Link]

3. Accelerating Online Reinforcement Learning via Model-Based Meta-Learning John D Co-Reyes, Sarah Feng, Glen Berseth, Jie Qui, and Sergey Levine In Learning to Learn - Workshop at ICLR 2021 [Link]

4. DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies Soroush Nasiriany, Vitchyr H. Pong, Ashvin Nair, Alexander Khazatsky, Glen Berseth, and Sergey Levine International Conference on Robotics and Automation (ICRA 2021) arXiv | [Link] Project Page |

5. Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation Charles Sun, Coline Devin, Brian Yang, Jędrzej Orbik, Abhishek Gupta, Glen Berseth, and Sergey Levine In Conference on Robot Learning (CoRL) Video |

6. SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, and Sergey Levine In International Conference on Learning Representations \textbf(Oral, top 1.8% of submissions) arXiv | [Link] Project Page | Video |

1. X2T: Training an X-to-Text Typing Interface with Online Learning from Implicit Feedback Jensen Gao, Sid Reddy, Glen Berseth, Anca Dragon, and Sergey Levine International Conference on Learning Representations (ICLR) 2021

2. Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, and Koushil Sreenath International Conference on Robotics and Automation (ICRA 2021)

3. Ecological Reinforcement Learning John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, and Sergey Levine CoRR [Link]

4. Gamification of Crowd-Driven Environment Design Michael Brandon Haworth, Muhammad Usman, Davide Schaumann, Nilay Chakraborty, Berseth Glen, Petros Faloutsos, and Mubbasir Kapadia IEEE Computer Graphics and Applications

5. Morphology-Agnostic Visual Robotic Control Brian Yang, Dinesh Jayaraman, Berseth Glen, Alexei Efros, and Sergey Levine IEEE Robotics and Automation Letters

6. Deep Integration of Physical Humanoid Control and Crowd Navigation (\textbfbest paper runner up) Berseth Glen *, Brandon Haworth*, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of the 13th International Conference on Motion in Games

1. Contextual Imagined Goals for Self-Supervised Robotic Learning Ashvin Nair^*, Shikhar Bahl^*, Alexander Khazatsky^*, Vitchyr Pong, Glen Berseth, and Sergey Levine In Conference on Robot Learning (CoRL) arXiv | Project Page | Video |

2. Interactive Architectural Design with Diverse Solution Exploration Glen Berseth, Brandon Haworth, Muhammad Usman, Davide Schaumann, Mahyar Khayatkhoei, Mubbasir Kapadia, and Petros Faloutsos IEEE Transactions on Visualization and Computer Graphics Video |

1. Terrain RL Simulator Glen Berseth, Xue Bin Peng, and Michiel Panne CoRR [Link]

2. Feedback Control For Cassie With Deep Reinforcement Learning Zhaoming Xie, Glen Berseth, Patrick Clary, Jonathan W. Hurst, and Michiel Panne In Proc. IEEE/RSJ Intl Conf on Intelligent Robots and Systems (IROS 2018)

3. Model-Based Action Exploration for Learning Dynamic Motion Skills Glen Berseth, Alex Kyriazis, Ivan Zinin, William Choi, and Michiel Panne In Proc. IEEE/RSJ Intl Conf on Intelligent Robots and Systems (IROS 2018) Video |

4. Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control Glen Berseth, Cheng Xie, Paul Cernek, and Michiel Van Panne International Conference on Learning Representations (ICLR) 2018 Video |

1. Evaluating and optimizing evacuation plans for crowd egress Vincius J Cassol, Estêvão Smania Testa, Cláudio Rosito Jung, Muhammad Usman, Petros Faloutsos, Berseth Glen, Mubbasir Kapadia, Norman I Badler, and Soraia Raupp Musse IEEE computer graphics and applications

2. Perceptual Evaluation of Space in Virtual Environments Muhammad Usman, Brandon Haworth, Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of the Tenth International Conference on Motion in Games

3. Crowd Sourced Co-design of Floor Plans Using Simulation Guided Games Nilay Chakraborty, Brandon Haworth, Muhammad Usman, Berseth Glen, Petros Faloutsos, and Mubbasir Kapadia In Proceedings of the Tenth International Conference on Motion in Games

4. On density flow relationships during crowd evacuation Brandon Haworth, Muhammad Usman, Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos Computer Animation and Virtual Worlds 28 (3-4)

5. DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning Xue Bin Peng, Berseth Glen, KangKang Yin, and Michiel Panne SIGGRAPH 2017

6. Understanding spatial perception and visual modes in the review of architectural designs Muhammad Usman, Brandon Haworth, Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 31

7. CODE: Crowd Optimized Design of Environments Brandon Haworth, Muhammad Usman, Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos Computer Animation and Virtual Worlds

1. ACCLMesh: curvature-based navigation mesh generation Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos Computer Animation and Virtual Worlds

2. Terrain-adaptive locomotion skills using deep reinforcement learning Xue Bin Peng, Berseth Glen, and Michiel Panne ACM Transactions on Graphics (TOG)

3. Using synthetic crowds to inform building pillar placements Brandon Haworth, Muhammad Usman, Berseth Glen, Mahyar Khayatkhoei, Mubbasir Kapadia, and Petros Faloutsos In Virtual Humans and Crowds for Immersive Environments (VHCIE), IEEE

4. Towards Computer Assisted Crowd Aware Architectural Design Brandon Haworth, Muhammad Usman, Berseth Glen, Mahyar Khayatkhoei, Mubbasir Kapadia, and Petros Faloutsos In CHI ’16 Extended Abstracts [Link]

1. Dynamic Terrain Traversal Skills Using Reinforcement Learning Xue Bin Peng, Berseth Glen, and Michiel Panne ACM Trans. Graph. [Link]

2. Environment optimization for crowd evacuation Berseth Glen, Muhammad Usman, Brandon Haworth, Mubbasir Kapadia, and Petros Faloutsos Computer Animation and Virtual Worlds [Link] Video |

3. Robust Space-Time Footsteps for Agent-Based Steering (best short paper) Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos Computer Animation and Virtual Worlds Video |

4. ACCLMesh: Curvature-based Navigation Mesh Generation Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games [Link]

5. Evaluating and Optimizing Level of Service for Crowd Evacuations Brandon Haworth, Muhammad Usman, Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games [Link]

1. Characterizing and Optimizing Game Level Difficulty Berseth Glen, M. Brandon Haworth, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of the Seventh International Conference on Motion in Games [Link]

2. SteerFit: Automated Parameter Fitting for Steering Algorithms Glen Berseth, Mubbasir Kapadia, Brandon Haworth, and Petros Faloutsos In Eurographics/ ACM SIGGRAPH Symposium on Computer Animation [Link]

1. SteerPlex: Estimating Scenario Complexity for Simulated Crowds Berseth Glen, Mubbasir Kapadia, and Petros Faloutsos In Proceedings of Motion on Games [Link]