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 (IROS, 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)

Siamese Encoding and Alignment by Multiscale Learning with Self-Supervision. - Eric Mitchell; Stefan Keselj; Sergiy Popovych; Davit Buniatyan; H. Sebastian Seung (CoRR, 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)

Higher-Order Function Networks for Learning Composable 3D Object Representations. - Eric Mitchell; Selim Engin; Volkan Isler; Daniel D. Lee (ICLR, 2020)

Higher Order Function Networks for View Planning and Multi-View Reconstruction. - Selim Engin; Eric Mitchell; Daewon Lee; Volkan Isler; Daniel D. Lee (ICRA, 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 (IJCAI, 2020)

Challenges of Acquiring Compositional Inductive Biases via Meta-Learning. - Eric Mitchell; Chelsea Finn; Christopher D. Manning (MetaDL@AAAI, 2021)

Geodesic-HOF: 3D Reconstruction Without Cutting Corners. - Ziyun Wang 001; Eric A. Mitchell; Volkan Isler; Daniel D. Lee (AAAI, 2021)

Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation. - Suraj Nair 003; Eric Mitchell; Kevin Chen 001; Brian Ichter; Silvio Savarese; Chelsea Finn (CoRL, 2021)

Offline Meta-Reinforcement Learning with Advantage Weighting. - Eric Mitchell; Rafael Rafailov; Xue Bin Peng; Sergey Levine; Chelsea Finn (ICML, 2021)

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 (EMNLP, 2022)

Fast Model Editing at Scale. - Eric Mitchell; Charles Lin; Antoine Bosselut; Chelsea Finn; Christopher D. Manning (ICLR, 2022)

Memory-Based Model Editing at Scale. - Eric Mitchell; Charles Lin; Antoine Bosselut; Christopher D. Manning; Chelsea Finn (ICML, 2022)

Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. - Peter Henderson 002; Eric Mitchell; Christopher D. Manning; Dan Jurafsky; Chelsea Finn (AIES, 2023)

Meta-Learning Online Adaptation of Language Models. - Nathan Hu; Eric Mitchell; Christopher D. Manning; Chelsea Finn (EMNLP, 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 (EMNLP, 2023)

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature. - Eric Mitchell; Yoonho Lee 001; Alexander Khazatsky; Christopher D. Manning; Chelsea Finn (ICML, 2023)

RECKONING: Reasoning through Dynamic Knowledge Encoding. - Zeming Chen 001; Gail Weiss; Eric Mitchell; Asli Celikyilmaz; Antoine Bosselut (NeurIPS, 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 (NeurIPS, 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 001; Mihai Christodorescu; Anupam Datta; Soheil Feizi; Kathleen Fisher; Tatsunori Hashimoto; et al. (CoRR, 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 001; Mihai Christodorescu; Anupam Datta; Soheil Feizi; Kathleen Fisher; Tatsunori Hashimoto; et al. (Found. Trends Priv. Secur., 2023)

Calibrating Language Models with Adaptive Temperature Scaling. - Johnathan Xie; Annie S. Chen; Yoonho Lee 001; Eric Mitchell; Chelsea Finn (EMNLP, 2024)

An Emulator for Fine-tuning Large Language Models using Small Language Models. - Eric Mitchell; Rafael Rafailov; Archit Sharma; Chelsea Finn; Christopher D. Manning (ICLR, 2024)

Language Model Detectors Are Easily Optimized Against. - Charlotte Nicks; Eric Mitchell; Rafael Rafailov; Archit Sharma; Christopher D. Manning; Chelsea Finn; Stefano Ermon (ICLR, 2024)

Fine-Tuning Language Models for Factuality. - Katherine Tian; Eric Mitchell; Huaxiu Yao; Christopher D. Manning; Chelsea Finn (ICLR, 2024)

RLVF: Learning from Verbal Feedback without Overgeneralization. - Moritz Stephan; Alexander Khazatsky; Eric Mitchell; Annie S. Chen; Sheryl Hsu; Archit Sharma; Chelsea Finn (ICML, 2024)

A Critical Evaluation of AI Feedback for Aligning Large Language Models. - Archit Sharma; Sedrick Scott Keh; Eric Mitchell; Chelsea Finn; Kushal Arora; Thomas Kollar (NeurIPS, 2024)

Online Adaptation of Language Models with a Memory of Amortized Contexts. - Jihoon Tack; Jaehyung Kim 001; Eric Mitchell; Jinwoo Shin; Yee Whye Teh; Jonathan Richard Schwarz (NeurIPS, 2024)

Test-Time Alignment via Hypothesis Reweighting. - Yoonho Lee 001; Jonathan Williams; Henrik Marklund; Archit Sharma; Eric Mitchell; Anikait Singh; Chelsea Finn (CoRR, 2024)

OpenAI o1 System Card. - Aaron Jaech; Adam Kalai; Adam Lerer; Adam Richardson; Ahmed El-Kishky; Aiden Low; Alec Helyar; Aleksander Madry; Alex Beutel; Alex Carney; Alex Iftimie; Alex Karpenko; et al. (CoRR, 2024)

FSPO: Few-Shot Preference Optimization of Synthetic Preference Data in LLMs Elicits Effective Personalization to Real Users. - Anikait Singh; Sheryl Hsu; Kyle Hsu; Eric Mitchell; Stefano Ermon; Tatsunori Hashimoto; Archit Sharma; Chelsea Finn (CoRR, 2025)