8 citations · 25 across the 8 of their papers we have counts for
5 papers · 1 filter
Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Construction
Hongbin Ye, Honghao Gui, Aijia Zhang +2
This paper introduces CooperKGC, a novel framework challenging the conventional solitary approach of large language models (LLMs) in knowledge graph construction (KGC). CooperKGC e…
FactCHD: Benchmarking Fact-Conflicting Hallucination Detection
Xiang Chen, Duanzheng Song, Honghao Gui +7
Despite their impressive generative capabilities, LLMs are hindered by fact-conflicting hallucinations in real-world applications. The accurate identification of hallucinations in…
Making Language Models Better Tool Learners with Execution Feedback
Shuofei Qiao, Honghao Gui, Chengfei Lv +3
Tools serve as pivotal interfaces that enable humans to understand and reshape the environment. With the advent of foundation models, AI systems can utilize tools to expand their c…
InstructIE: A Bilingual Instruction-based Information Extraction Dataset
Honghao Gui, Shuofei Qiao, Jintian Zhang +6
Large language models can perform well on general natural language tasks, but their effectiveness is still suboptimal for information extraction (IE). Recent works indicate that th…
Schema-adaptable Knowledge Graph Construction
Hongbin Ye, Honghao Gui, Xin Xu +3
Conventional Knowledge Graph Construction (KGC) approaches typically follow the static information extraction paradigm with a closed set of pre-defined schema. As a result, such ap…