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YAYI-UIE: A Chat-Enhanced Instruction Tuning Framework for Universal Information Extraction
April 3, 2024, 4:47 a.m. | Xinglin Xiao, Yijie Wang, Nan Xu, Yuqi Wang, Hanxuan Yang, Minzheng Wang, Yin Luo, Lei Wang, Wenji Mao, Daniel Zeng
cs.CL updates on arXiv.org arxiv.org
Abstract: The difficulty of the information extraction task lies in dealing with the task-specific label schemas and heterogeneous data structures. Recent work has proposed methods based on large language models to uniformly model different information extraction tasks. However, these existing methods are deficient in their information extraction capabilities for Chinese languages other than English. In this paper, we propose an end-to-end chat-enhanced instruction tuning framework for universal information extraction (YAYI-UIE), which supports both Chinese and English. …
abstract arxiv chat cs.ai cs.cl data extraction framework however information information extraction language language models large language large language models lies tasks the information type universal work
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