AI RESEARCH
When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables
arXiv CS.CL
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ArXi:2509.17680v2 Announce Type: replace Table question answering (TableQA) is a fundamental task in natural language processing (NLP). The strong reasoning capabilities of large language models (LLMs) have brought significant advances in this field. However, as real-world applications involve increasingly complex questions and larger tables, substantial noisy data is