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Awesome-RLHF
Awesome Reinforcement Learning from Human Feedback, the secret behind ChatGPT XD
https://github.com/andy-yangz/Awesome-RLHF
- Illustrating Reinforcement Learning from Human Feedback (RLHF)
- TAMER: Training an Agent Manually via Evaluative Reinforcement
- Interactive Learning from Policy-Dependent Human Feedback
- Deep Reinforcement Learning from Human Preferences - through-human-feedback)]
- Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces
- Fine-Tuning Language Models from Human Preferences - human-preferences)]
- Learning to summarize with human feedback
- Recursively Summarizing Books with Human Feedback
- WebGPT: Browser-assisted question-answering with human feedback
- Training language models to follow instructions with human feedback
- Teaching language models to support answers with verified quotes
- Improving alignment of dialogue agents via targeted human judgements
- ChatGPT: Optimizing Language Models for Dialogue
- Scaling Laws for Reward Model Overoptimization
- Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
- Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
- Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning
- Is Reinforcement Learning (Not) for Natural Language Processing?: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
- Offline RL for Natural Language Generation with Implicit Language Q Learning - Snell/Implicit-Language-Q-Learning)]
- Transformer Reinforcement Learning (TRL)
- Transformer Reinforcement Learning X (TRLX) - Learning*** (**ILQL**)
- RL4LMs (A modular RL library to fine-tune language models to human preferences)
- HH-RLHF - rlhf)]：A Dataset created by Anthropic.
- Learning Task Specifications for Reinforcement Learning from Human Feedback
- Reinforcement Learning from Human Feedback: From Zero to chatGPT