AI RESEARCH
MATA: Multi-Agent Framework for Reliable and Flexible Table Question Answering
arXiv CS.AI
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ArXi:2602.09642v2 Announce Type: replace-cross Recent advances in Large Language Models (LLMs) have significantly improved table understanding tasks such as Table Question Answering (TableQA), yet challenges remain in ensuring reliability, scalability, and efficiency, especially in resource-constrained or privacy-sensitive environments. In this paper, we