1 citations · 1 across the 3 of their papers we have counts for
4 papers
Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Exploration
Chuangtao Ma, Zeyu Zhang, Arijit Khan +2
Retrieval-augmented generation (RAG) enhances LLM reasoning in knowledge-intensive tasks, but existing RAG pipelines incur substantial retrieval and generation overhead when applie…
MetaToolAgent: Towards Generalizable Tool Usage in LLMs through Meta-Learning
Zheng Fang, Wolfgang Mayer, Zeyu Zhang +4
Tool learning is increasingly important for large language models (LLMs) to effectively coordinate and utilize a diverse set of tools in order to solve complex real-world tasks. By…
LAMP: Extracting Local Decision Surfaces From Large Language Models
Ryan Chen, Youngmin Ko, Zeyu Zhang +5
We introduce LAMP (Local Attribution Mapping Probe), a method that shines light onto a black-box language model's decision surface and studies how reliably a model maps its stated…
AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language Model
Zeyu Zhang, Paul Groth, Iacer Calixto +1
Entity matching (EM) is the problem of determining whether two records refer to same real-world entity, which is crucial in data integration, e.g., for product catalogs or address…