Direct Preference Optimization: Your Language Model is Secretly a Reward Model | DPO paper explained

Direct Preference Optimization (DPO) to finetune LLMs without reinforcement learning. DPO was one of the two Outstanding Main Track Runner-Up papers.
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📜 Rafailov, Rafael, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, and Chelsea Finn. "Direct preference optimization: Your language model is secretly a reward model." arXiv preprint arXiv:2305.18290 (2023). https://arxiv.org/abs/2305.18290

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Outline:
00:00 DPO motivation
00:53 Finetuning with human feedback
01:39 RLHF explained
03:05 DPO explained
04:24 Why Reinforcement Learning in the first place?
05:58 Shortcomings
06:50 Results

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