2307.12950.pdf

N/A

Published as a conference paper at ICLR 2024 RLCD: R EINFORCEMENT L EARNING FROM C ON - TRASTIVE D ISTILLATION FOR LM A LIGNMENT Kevin Yang1,2 Dan Klein2 Asli Celikyilmaz1 Nanyun Peng3 Yuandong Tian1 1 Meta AI, 2 UC Berkeley, 3 UCLA {yangk,klein}@berkeley.edu,{aslic,yuandong}@meta.com,violetpeng@cs.ucla.edu…

saved by

• sashrika pandey

related reading

• 2310.12921.pdfarxiv.org
• [2305.18290] Direct Preference Optimization: Your Language Model is Secretly a Reward Modelarxiv.org
• Illustrating Reinforcement Learning from Human Feedback (RLHF)huggingface.co
• [2510.13786] The Art of Scaling Reinforcement Learning Compute for LLMsarxiv.org
• [2309.00267] RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedbackarxiv.org
• 2401.10020.pdfarxiv.org
• [2302.08582] Pretraining Language Models with Human Preferencesarxiv.org
• [2203.02155] Training language models to follow instructions with human feedbackarxiv.org
• 2308.03958arxiv.org
• [2402.14740] Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMsarxiv.org
• Language Models can Solve Computer Tasksarxiv.org
• Training language models to follow instructions with human feedback.pdfproceedings.neurips.cc