Illustrating Reinforcement Learning from Human Feedback (RLHF)

Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases

Reinforcement Learning from Human Feedback (RLHF) is the standard method to align Large Language Models (LLMs) with human preferences. In this work, we introduce alignment tampering, a potential vulnerability where the LLM undergoing alignment influences the preference dataset, causing RLHF to amplify undesired beha...

An Introduction to Deep Reinforcement Learning

Introducing ⚔️ AI vs. AI ⚔️ a deep reinforcement learning multi-agents competition system

Putting RL back in RLHF

Federated Learning using Hugging Face and Flower

Migrating the Hub from Git LFS to Xet