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Reinforcement Learning of Large Language Models

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[UCLA RL-LLM] Chapter 2.4: In-context learning and instruction fine-tuning

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[UCLA RL-LLM] Chapter 2.3: Transformers II (modern transformers updates and sampling methods)

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[UCLA RL-LLM] Chapter 2.2: Transformers I (BERT, GPT-1)

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[UCLA RL-LLM] Chapter 2.1: NLP foundations, language modeling, RNNs

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[UCLA RL-LLM] Chapter 3.2: Reinforcement learning with verifiable rewards (RLVR)

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[UCLA RL-LLM] Chapter 3.1: Reinforcement learning from human feedback (PPO, DPO)

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[UCLA RL-LLM] Chapter 1.5: AlphaGo, test-time compute, and expert iteration

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[UCLA RL-LLM] Chapter 1.4: Deep policy gradient methods (PPO, GRPO)

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[UCLA RL-LLM] Chapter 1.3: Deep policy gradient methods (A3C)

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[UCLA RL-LLM] Chapter 1.2: Deep policy evaluation

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[UCLA RL-LLM] Chapter 1.1: MDP foundations, imitation learning, and value iteration

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[UCLA RL-LLM] Chapter 0: Course outline and prologue

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