These slides are only for reference purpose.

• The crucial role of samplers in online direct preference optimization

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• Logit mixing and RLHF paper reading

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• Decoding-time language model alignment with multiple objectives

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• Unleashing the power of pre-trained language models for offline reinforcement learning

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