Software Engineering And Web Development: RLAIF Outperforms RLHF
RLAIF outperforms RLHF in aligning LLMs with human preferences, offering a scalable solution to costly human feedback.
This is a Plain English Papers summary of a research paper called AI Feedback Scaling Human-Aligned Language Models: RLAIF Outperforms RLHF. If you like these kinds of analysis, you should join AImodels.fyi or follow me on Twitter. Overview Reinforcement learning from human feedback (RLHF) has been effective in aligning large language models (LLMs) with human preferences. However, gathering high-quality preference labels from humans is expensive. Reinforcement Learning from AI Feedback (RLAIF) offers a promising alternative that trains the reward model (RM) on preferences generated b...