Evan Zheran Liu

According to our database, Evan Zheran Liu authored at least 16 papers between 2017 and 2024.

Collaborative distances:

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

2024

AutoBencher: Creating Salient, Novel, Difficult Datasets for Language Models.

Xiang Lisa Li, Evan Zheran Liu, Percy Liang, Tatsunori Hashimoto

CoRR, 2024

A Fast and Accurate Machine Learning Autograder for the Breakout Assignment.

Evan Zheran Liu, David Yuan, Ahmed Ahmed, Elyse Cornwall, Juliette Woodrow, Kaylee Burns, Allen Nie, Emma Brunskill, Chris Piech, Chelsea Finn

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Learning to Explore in POMDPs with Informational Rewards.

Annie Xie, Logan M. Bhamidipaty, Evan Zheran Liu, Joey Hong, Sergey Levine, Chelsea Finn

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A Survey of Meta-Reinforcement Learning.

Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson

CoRR, 2023

Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning.

Evan Zheran Liu, Sahaana Suri, Tong Mu, Allan Zhou, Chelsea Finn

Proceedings of the International Conference on Machine Learning, 2023

2022

Giving Feedback on Interactive Student Programs with Meta-Exploration.

Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn

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

Learning Options via Compression.

Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn

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

2021

Analyzing a Caching Model.

Leon Sixt, Evan Zheran Liu, Marie Pellat, James Wexler, Milad Hashemi, Been Kim, Martin Maas

CoRR, 2021

Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices.

Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn

Proceedings of the 38th International Conference on Machine Learning, 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

2020

Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning.

Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn

CoRR, 2020

Learning Abstract Models for Strategic Exploration and Fast Reward Transfer.

Evan Zheran Liu, Ramtin Keramati, Sudarshan Seshadri, Kelvin Guu, Panupong Pasupat, Emma Brunskill, Percy Liang

CoRR, 2020

An Imitation Learning Approach for Cache Replacement.

Evan Zheran Liu, Milad Hashemi, Kevin Swersky, Parthasarathy Ranganathan, Junwhan Ahn

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Reinforcement Learning on Web Interfaces using Workflow-Guided Exploration.

Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, Tianlin Shi, Percy Liang

Proceedings of the 6th International Conference on Learning Representations, 2018

Mapping natural language commands to web elements.

Panupong Pasupat, Tian-Shun Jiang, Evan Zheran Liu, Kelvin Guu, Percy Liang

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood.

Kelvin Guu, Panupong Pasupat, Evan Zheran Liu, Percy Liang

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017