LLM2 DPO: Training A Language Model To Satisfy Human Preferences Direct Preference Optimization:Your Language Model is Secretly a Reward ModelRafael Rafailov∗† Archit Sharma∗† Eric Mitchell∗† Stefano Ermon†‡ Christopher D. Manning† Chelsea Finn†13 Dec 2023 Policy Preferred by HumansLarge-scale unsupervised language models are known to solve various tasks based on extensive knowledges. These generative models produce responses based on their policy. RLHF (Rei.. 2024. 7. 4. KMMLU: A Korean Benchmark for LLMs KMMLU: Measuring Massive Multitask Language Understanding in Korean Guijin Son, Hanwool Lee, Sungdong Kim, etc. 18 Feb 2024 MMLU There exist various benchmarks for evaluating and understanding the capabilities of Large Language Models (LLMs), such as commonsense reasoning, code generation, and multi-turn conversations. Massive Multitask Language Understanding (MMLU) is one of these benchmarks, c.. 2024. 3. 29. 이전 1 다음