Direct Preference Optimization (DPO) to finetune LLMs without reinforcement learning. DPO was one of the two Outstanding Main Track Runner-Up papers.
➡️ AI Coffee Break Merch! 🛍️ https://aicoffeebreak.creator-spring....

📜 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

Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏
Dres. Trost GbR, Siltax, Vignesh Valliappan, ‪@Mutual_Information‬ , Kshitij

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

▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕
Patreon:   / aicoffeebreak  
Ko-fi: https://ko-fi.com/aicoffeebreak
▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

🔗 Links:
AICoffeeBreakQuiz:    / aicoffeebreak  
Twitter:   / aicoffeebreak  
Reddit:   / aicoffeebreak  
YouTube:    / aicoffeebreak  

#AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​

Video editing: Nils Trost
Music 🎵 : Ice & Fire - King Canyon