Eric Mitchell

According to our database, Eric Mitchell authored at least 29 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Online Adaptation of Language Models with a Memory of Amortized Contexts.

Jihoon Tack, Jaehyung Kim, Eric Mitchell, Jinwoo Shin, Yee Whye Teh, Jonathan Richard Schwarz

CoRR, 2024

A Critical Evaluation of AI Feedback for Aligning Large Language Models.

Archit Sharma, Sedrick Keh, Eric Mitchell, Chelsea Finn, Kushal Arora, Thomas Kollar

CoRR, 2024

RLVF: Learning from Verbal Feedback without Overgeneralization.

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

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

Fine-Tuning Language Models for Factuality.

Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Language Model Detectors Are Easily Optimized Against.

Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D. Manning, Chelsea Finn, Stefano Ermon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

An Emulator for Fine-tuning Large Language Models using Small Language Models.

Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher D. Manning

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Calibrating Language Models with Adaptive Temperature Scaling.

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

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Identifying and Mitigating the Security Risks of Generative AI.

Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang

Found. Trends Priv. Secur., 2023

Identifying and Mitigating the Security Risks of Generative AI.

Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang

CoRR, 2023

Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RECKONING: Reasoning through Dynamic Knowledge Encoding.

Zeming Chen, Gail Weiss, Eric Mitchell, Asli Celikyilmaz, Antoine Bosselut

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature.

Eric Mitchell, Yoonho Lee, Alexander Khazatsky, Christopher D. Manning, Chelsea Finn

Proceedings of the International Conference on Machine Learning, 2023

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Meta-Learning Online Adaptation of Language Models.

Nathan Hu, Eric Mitchell, Christopher D. Manning, Chelsea Finn

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models.

Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Memory-Based Model Editing at Scale.

Eric Mitchell, Charles Lin, Antoine Bosselut, Christopher D. Manning, Chelsea Finn

Proceedings of the International Conference on Machine Learning, 2022

Fast Model Editing at Scale.

Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher D. Manning

Proceedings of the Tenth International Conference on Learning Representations, 2022

Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference.

Eric Mitchell, Joseph J. Noh, Siyan Li, William S. Armstrong, Ananth Agarwal, Patrick Liu, Chelsea Finn, Christopher D. Manning

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Offline Meta-Reinforcement Learning with Advantage Weighting.

Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn

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

Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation.

Suraj Nair, Eric Mitchell, Kevin Chen, Brian Ichter, Silvio Savarese, Chelsea Finn

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Geodesic-HOF: 3D Reconstruction Without Cutting Corners.

Ziyun Wang, Eric A. Mitchell, Volkan Isler, Daniel D. Lee

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Challenges of Acquiring Compositional Inductive Biases via Meta-Learning.

Eric Mitchell, Chelsea Finn, Christopher D. Manning

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020

Reward Prediction Error as an Exploration Objective in Deep RL.

Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Higher Order Function Networks for View Planning and Multi-View Reconstruction.

Selim Engin, Eric Mitchell, Daewon Lee, Volkan Isler, Daniel D. Lee

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Higher-Order Function Networks for Learning Composable 3D Object Representations.

Eric Mitchell, Selim Engin, Volkan Isler, Daniel D. Lee

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

QXplore: Q-learning Exploration by Maximizing Temporal Difference Error.

Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee

CoRR, 2019

Siamese Encoding and Alignment by Multiscale Learning with Self-Supervision.

Eric Mitchell, Stefan Keselj, Sergiy Popovych, Davit Buniatyan, H. Sebastian Seung

CoRR, 2019

Q-Learning for Continuous Actions with Cross-Entropy Guided Policies.

Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee

CoRR, 2019

Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner.

Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019