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His books tend to be dry and geared towards researchers, in my opinion. He has a new one on RL: https://web.mit.edu/dimitrib/www/RLCOURSECOMPLETE%202ndEDITI...


I'm looking for content (researcher myself) -- mainly on the application side. Should I start with this one? Or anything else?

Very curious about RL for LLMs for example (using data from real use).


I have not read it but it looks like a comprehensive reference. For a more applied treatment see Foundations of Deep Reinforcement Learning. https://slm-lab.gitbook.io/slm-lab/publications-and-talks/in...

Neither cover LLMs. I don't follow the literature closely so I can only suggest you read papers: https://github.com/WindyLab/LLM-RL-Papers




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