Reinforcement Learning in the Era of LLMs
Deep Papers
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Mapping Reinforcement Learning Principles to Language Models
Exploring the application of reinforcement learning concepts in Language Models including credit assignment, decision-making processes, token selection, and user feedback for adjusting model parameters. The chapter delves into the challenges of working with long documents, latency issues in reinforcement learning, and the role of automated feedback signals.
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