BriefGPT.xyz
Nov, 2023
针对事实性的语言模型微调
Fine-tuning Language Models for Factuality
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Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn
TL;DR
通过利用外部知识库的一致性或大模型的置信度,以及直接优化算法,我们在不需要人工标注的情况下,对语言模型进行微调,明显提高了生成候选项的正确性,并比对准确性进行了目标定向的RLHF和解码策略有显著改善。
Abstract
The fluency and creativity of large pre-trained
language models
(LLMs) have led to their widespread use, sometimes even as a replacement for traditional search engines. Yet
language models
are prone to making con
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