Rafael Rafailov

According to our database, Rafael Rafailov authored at least 15 papers between 2021 and 2024.

Collaborative distances:

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

2024

Disentangling Length from Quality in Direct Preference Optimization.

Ryan Park, Rafael Rafailov, Stefano Ermon, Chelsea Finn

CoRR, 2024

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning.

Yiyang Zhou, Chenhang Cui, Rafael Rafailov, Chelsea Finn, Huaxiu Yao

CoRR, 2024

2023

Diffusion Model Alignment Using Direct Preference Optimization.

Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik

CoRR, 2023

Contrastive Preference Learning: Learning from Human Feedback without RL.

Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh

CoRR, 2023

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

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

CoRR, 2023

Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias.

Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn

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

Contrastive Example-Based Control.

Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

Proceedings of the Learning for Dynamics and Control Conference, 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

MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning.

Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn

Proceedings of the Conference on Robot Learning, 2023

2022

Vision-Based Manipulators Need to Also See from Their Hands.

Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, Chelsea Finn

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

COMBO: Conservative Offline Model-Based Policy Optimization.

Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Visual Adversarial Imitation Learning using Variational Models.

Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Offline Reinforcement Learning from Images with Latent Space Models.

Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 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