Tag
RLHF
Posts and notes tagged with RLHF.
- June 20, 202616 min read
REINFORCE Leave-One-Out (RLOO)
How RLOO replaces PPO in RLHF with the simplest policy gradient: treating the whole response as one action, using REINFORCE, and comparing each response with the average reward of the other responses to the same prompt.
- May 13, 202619 min read
Direct Preference Optimization (DPO)
How Direct Preference Optimization (DPO) aligns language models with human preferences without a reward model or reinforcement learning, by turning the RLHF objective into a simple classification loss. Part 5 of a series on policy optimization for LLMs.
- March 21, 202627 min read
Reinforcement Learning from Human Feedback (RLHF)
How Reinforcement Learning from Human Feedback (RLHF) trains language models from human preferences: collecting comparisons, training a reward model, and optimizing the model with PPO under a KL penalty. Part 4 of a series on policy optimization for LLMs.
- March 10, 202635 min read
Proximal Policy Optimization (PPO)
How Proximal Policy Optimization (PPO) achieves the stability of TRPO with a simple clipped objective and first-order optimization, explained step by step: the advantage function, the value model, Monte Carlo and temporal difference estimates, GAE, the probability ratio, and clipping. Part 3 of a series on policy optimization for LLMs.
- February 14, 20268 min read
Reinforcement Learning for LLMs: SFT to Policy Gradients
Why supervised fine-tuning is not enough to align large language models, how reinforcement learning maps onto an LLM, and why the vanilla policy gradient is unstable. Part 1 of a series on policy optimization for LLMs.