Sebastian Raschka • 3/31/2024

Tips for LLM Pretraining and Evaluating Reward Models

This technical article analyzes recent AI research, focusing on two key papers. It first explores scalable strategies for continually pretraining large language models (LLMs) to update them with new knowledge or adapt them to new domains. It then discusses reward modeling used in Reinforcement Learning from Human Feedback (RLHF) for aligning LLMs with human preferences and a new benchmark for evaluation.

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#AI Research #Reinforcement Learning #LLM Pretraining