most citedAgent-OM: Leveraging LLM Agents for Ontology Matching

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

cs.AI20264 cited

Agent-OM: Leveraging LLM Agents for Ontology Matching

Zhangcheng Qiang, Weiqing Wang, Kerry Taylor

Ontology matching (OM) enables semantic interoperability between different ontologies and resolves their conceptual heterogeneity by aligning related entities. OM systems currently…

cs.IR2026

Crowd-OM: Crowdsourcing for Ontology Matching Validation

Zhangcheng Qiang, Weiqing Wang, Kerry Taylor

Recent advances in large language models (LLMs) pose new challenges for ontology matching (OM). While OM systems built on LLMs have shown remarkable capabilities in discovering mor…

cs.CL2026

How Does A Text Preprocessing Pipeline Affect Ontology Matching?

Zhangcheng Qiang, Kerry Taylor, Weiqing Wang

The classical text preprocessing pipeline, comprising Tokenisation, Normalisation, Stop Words Removal, and Stemming/Lemmatisation, has been implemented in many systems for ontology…

cs.AI2026

OAEI-LLM: A Benchmark Dataset for Understanding Large Language Model Hallucinations in Ontology Matching

Zhangcheng Qiang, Kerry Taylor, Weiqing Wang +1

Hallucinations of large language models (LLMs) commonly occur in domain-specific downstream tasks, with no exception in ontology matching (OM). The prevalence of using LLMs for OM…

cs.AI2025

OAEI-LLM-T: A TBox Benchmark Dataset for Understanding Large Language Model Hallucinations in Ontology Matching

Zhangcheng Qiang, Kerry Taylor, Weiqing Wang +1

Hallucinations are often inevitable in downstream tasks using large language models (LLMs). To tackle the substantial challenge of addressing hallucinations for LLM-based ontology…