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cs.CL2024
AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Framework
Meihao Fan, Ju Fan, Nan Tang +3
Answering natural language (NL) questions about tables, known as Tabular Question Answering (TQA), is crucial because it allows users to quickly and efficiently extract meaningful…
cs.CL2023★ 3 cited
Cost-Effective In-Context Learning for Entity Resolution: A Design Space Exploration
Meihao Fan, Xiaoyue Han, Ju Fan +4
Entity resolution (ER) is an important data integration task with a wide spectrum of applications. The state-of-the-art solutions on ER rely on pre-trained language models (PLMs),…