🧑‍🔬 Chelsea Finn — all works

51 works · ← Chelsea Finn

1. Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksarXiv:1703.03400Chelsea Finn, Pieter Abbeel, Sergey Levine2017 · 6,549 citations
2. Direct Preference Optimization: Your Language Model is Secretly a Reward ModelarXiv:2305.18290Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.2023 · 2,896 citations
3. End-to-End Training of Deep Visuomotor Policies ↗arXiv:1504.00702 · no summary yetSergey Levine et al.2015 · 1,463 citations
4. Do As I Can, Not As I Say: Grounding Language in Robotic AffordancesarXiv:2204.01691Michael Ahn, Anthony Brohan, Noah Brown, et al.2022 · 941 citations
5. DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability CurvaturearXiv:2301.11305Eric Mitchell, Yoonho Lee, Alexander Khazatsky, et al.2023 · 481 citations
6. Deep Spatial Autoencoders for Visuomotor Learning ↗arXiv:1509.06113 · no summary yetChelsea Finn et al.2015 · 461 citations
7. Model-Based Reinforcement Learning for Atari ↗arXiv (Cornell University) · no summary yetŁukasz Kaiser et al.2019 · 429 citations
8. WILDS: A Benchmark of in-the-Wild Distribution Shifts ↗CaltechAUTHORS (California Institute of Technology) · no summary yetPang Wei Koh et al.2020 · 405 citations
9. Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetKatherine Tian et al.2023 · 393 citations
10. Fast Model Editing at Scale ↗arXiv:2110.11309 · no summary yetEric Mitchell et al.2021 · 332 citations
11. MOPO: Model-based Offline Policy Optimization ↗arXiv (Cornell University) · no summary yetTianhe Yu et al.2020 · 260 citations
12. Memory-Based Model Editing at Scale ↗arXiv:2206.06520 · no summary yetEric Mitchell et al.2022 · 255 citations
13. OpenVLA: An Open-Source Vision-Language-Action Model ↗arXiv:2406.09246 · no summary yetMoo Jin Kim et al.2024 · 254 citations
14. Gradient Surgery for Multi-Task LearningarXiv:2001.06782Tianhe Yu, Saurabh Kumar, Abhishek Gupta, et al.2020 · 233 citations
15. Open X-Embodiment: Robotic Learning Datasets and RT-X Models ↗arXiv:2310.08864 · no summary yetEmbodiment Collaboration et al.2023 · 204 citations
16. Recasting Gradient-Based Meta-Learning as Hierarchical Bayes ↗arXiv (Cornell University) · no summary yetErin Grant et al.2018 · 165 citations
17. Analyzing and Mitigating Object Hallucination in Large Vision-Language Models ↗arXiv:2310.00754 · no summary yetYiyang Zhou et al.2023 · 134 citations
18. Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success ↗no summary yetMoo Jin Kim, Chelsea Finn, Percy Liang2025 · 132 citations
19. Fine-tuning Language Models for FactualityarXiv:2311.08401Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.2023 · 127 citations
20. Just Train Twice: Improving Group Robustness without Training Group Information ↗arXiv (Cornell University) · no summary yetEvan Zheran Liu et al.2021 · 125 citations
21. Adapting Deep Visuomotor Representations with Weak Pairwise Constraints ↗Springer proceedings in advanced robotics · no summary yetEric Tzeng et al.2015 · 124 citations
22. FAST: Efficient Action Tokenization for Vision-Language-Action ModelsarXiv:2501.09747Karl Pertsch, Kyle Stachowicz, Brian Ichter, et al.2025 · 123 citations
23. Disentangling Length from Quality in Direct Preference OptimizationFindings of the Association for Computational LinguisticsRyan Park, Rafael Rafailov, Stefano Ermon, et al.2024 · 105 citations
24. Language-Driven Representation Learning for Robotics ↗arXiv:2302.12766 · no summary yetSiddharth Karamcheti et al.2023 · 88 citations
25. From r to Q*: Your Language Model is Secretly a Q-Function ↗arXiv:2404.12358 · no summary yetRafael Rafailov et al.2024 · 72 citations
26. Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents ↗arXiv:2408.07199 · no summary yetPranav Putta et al.2024 · 68 citations
27. Surgical Fine-Tuning Improves Adaptation to Distribution Shifts ↗arXiv (Cornell University) · no summary yetYoonho Lee et al.2022 · 67 citations
28. Generative Reward Models ↗arXiv:2410.12832 · no summary yetDakota Mahan et al.2024 · 58 citations
29. Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data ↗arXiv (Cornell University) · no summary yetFahim Tajwar et al.2024 · 54 citations
30. Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference ↗Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yetEric Mitchell et al.2022 · 53 citations
31. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought ↗arXiv:2501.04682 · no summary yetViolet Xiang et al.2025 · 47 citations
32. An Emulator for Fine-Tuning Large Language Models using Small Language ModelsarXiv:2310.12962Eric Mitchell, Rafael Rafailov, Archit Sharma, et al.2023 · 36 citations
33. Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models ↗Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yetPeter B. Henderson et al.2023 · 36 citations
34. Meta-Inverse Reinforcement Learning with Probabilistic Context Variables ↗arXiv (Cornell University) · no summary yetLantao Yu et al.2019 · 30 citations
35. Meta-Learning Online Adaptation of Language Models ↗arXiv:2305.15076 · no summary yetNathan Hu et al.2023 · 22 citations
36. PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs ↗arXiv (Cornell University) · no summary yetSoroush Nasiriany et al.2024 · 21 citations
37. Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning ↗arXiv (Cornell University) · no summary yetMoo Jin Kim et al.2026 · 19 citations
38. Extending the WILDS Benchmark for Unsupervised Adaptation ↗arXiv (Cornell University) · no summary yetShiori Sagawa et al.2021 · 18 citations
39. Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices ↗arXiv (Cornell University) · no summary yetEvan Zheran Liu et al.2020 · 14 citations
40. Weakly-Supervised Reinforcement Learning for Controllable Behavior ↗arXiv (Cornell University) · no summary yetLisa Lee et al.2020 · 7 citations
41. RoboReward: General-Purpose Vision-Language Reward Models for Robotics ↗arXiv (Cornell University) · no summary yetTony Lee et al.2026 · 6 citations
42. LLM-as-a-Verifier: A General-Purpose Verification Framework ↗arXiv (Cornell University) · no summary yetJacky Kwok et al.2026 · 5 citations
43. FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users ↗arXiv (Cornell University) · no summary yetAnikait Singh et al.2025 · 5 citations
44. MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance ↗arXiv (Cornell University) · no summary yetMichael Luo et al.2021 · 4 citations
45. RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems ↗arXiv (Cornell University) · no summary yetQu, Yuxiao et al.2025 · 3 citations
46. Challenges of Acquiring Compositional Inductive Biases via Meta-Learning ↗National Conference on Artificial Intelligence · no summary yetEric Mitchell, Chelsea Finn, Christopher D. Manning2021 · 3 citations
47. Learning Compact Convolutional Neural Networks with Nested Dropout ↗arXiv (Cornell University) · no summary yetChelsea Finn, Lisa Anne Hendricks, Trevor Jackson Darrell2014 · 3 citations
48. VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model ↗arXiv (Cornell University) · no summary yetYanjiang Guo et al.2026
49. ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research ↗arXiv (Cornell University) · no summary yetSohyeon Kim et al.2026
50. Contrastive Example-Based Control ↗arXiv (Cornell University) · no summary yetKyle Hatch et al.2023
51. End-toend training of deep visuomotor policies. arXiv preprint arXiv:1504.00702 ↗no summary yetSergey Levine et al.2015

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