METEOR combines weak-to-strong distillation, iterative GPT-4 feedback, and contrastive self-training to adapt 7B-8B LLMs to a domain, with gains measured only by GPT-4 as judge.
In Findings of the Associa- tion for Computational Linguistics: EMNLP 2023, Singapore, December 6-10, 2023, pages 2550–2575
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METEOR: Evolutionary Journey of Large Language Models from Guidance to Self-Growth
METEOR combines weak-to-strong distillation, iterative GPT-4 feedback, and contrastive self-training to adapt 7B-8B LLMs to a domain, with gains measured only by GPT-4 as judge.