Annie S. Chen

According to our database, Annie S. Chen authored at least 13 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning.

Johnathan Xie, Yoonho Lee, Annie S. Chen, Chelsea Finn

CoRR, 2024

RLVF: Learning from Verbal Feedback without Overgeneralization.

Moritz Stephan, Alexander Khazatsky, Eric Mitchell, Annie S. Chen, Sheryl Hsu, Archit Sharma, Chelsea Finn

CoRR, 2024

AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data.

Caroline Choi, Yoonho Lee, Annie S. Chen, Allan Zhou, Aditi Raghunathan, Chelsea Finn

CoRR, 2024

2023

Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment.

Annie S. Chen, Govind Chada, Laura M. Smith, Archit Sharma, Zipeng Fu, Sergey Levine, Chelsea Finn

CoRR, 2023

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts.

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

CoRR, 2023

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

CoRR, 2023

Language-Driven Representation Learning for Robotics.

Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

You Only Live Once: Single-Life Reinforcement Learning.

Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Batch Exploration With Examples for Scalable Robotic Reinforcement Learning.

Annie S. Chen, HyunJi Nam, Suraj Nair, Chelsea Finn

IEEE Robotics Autom. Lett., 2021

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.

CoRR, 2021

Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos.

Annie S. Chen, Suraj Nair, Chelsea Finn

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Just Train Twice: Improving Group Robustness without Training Group Information.

Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn

Proceedings of the 38th International Conference on Machine Learning, 2021