149 citations · 163 across the 9 of their papers we have counts for
4 papers · 1 filter
Potential and Limitations of LLMs in Capturing Structured Semantics: A Case Study on SRL
Ning Cheng, Zhaohui Yan, Ziming Wang +6
Large Language Models (LLMs) play a crucial role in capturing structured semantics to enhance language understanding, improve interpretability, and reduce bias. Nevertheless, an on…
An In-depth Survey of Large Language Model-based Artificial Intelligence Agents
Pengyu Zhao, Zijian Jin, Ning Cheng
Due to the powerful capabilities demonstrated by large language model (LLM), there has been a recent surge in efforts to integrate them with AI agents to enhance their performance.…
CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction
Xiang Wei, Yufeng Chen, Ning Cheng +3
In order to construct or extend entity-centric and event-centric knowledge graphs (KG and EKG), the information extraction (IE) annotation toolkit is essential. However, existing I…
ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT
Xiang Wei, Xingyu Cui, Ning Cheng +9
Zero-shot information extraction (IE) aims to build IE systems from the unannotated text. It is challenging due to involving little human intervention. Challenging but worthwhile,…