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Exploring The Impact Of Table-to-text Methods On Augmenting Llm-based Question Answering With Domain Hybrid Data

Abstract

Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, including text and semi-structured tables, posing challenges for the seamless integration of information. Table-to-Text Generation is a promising solution by facilitating the transformation of hybrid data into a uniformly

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