5 citations · 7 across the 4 of their papers we have counts for
4 papers
Untangle the KNOT: Interweaving Conflicting Knowledge and Reasoning Skills in Large Language Models
Yantao Liu, Zijun Yao, Xin Lv +5
Providing knowledge documents for large language models (LLMs) has emerged as a promising solution to update the static knowledge inherent in their parameters. However, knowledge i…
Evaluating Generative Language Models in Information Extraction as Subjective Question Correction
Yuchen Fan, Yantao Liu, Zijun Yao +3
Modern Large Language Models (LLMs) have showcased remarkable prowess in various tasks necessitating sophisticated cognitive behaviors. Nevertheless, a paradoxical performance disc…
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction
Zixuan Li, Yutao Zeng, Yuxin Zuo +14
In this paper, we propose KnowCoder, a Large Language Model (LLM) to conduct Universal Information Extraction (UIE) via code generation. KnowCoder aims to develop a kind of unified…
Retrieval-Augmented Code Generation for Universal Information Extraction
Yucan Guo, Zixuan Li, Xiaolong Jin +8
Information Extraction (IE) aims to extract structural knowledge (e.g., entities, relations, events) from natural language texts, which brings challenges to existing methods due to…