作者位次 #5/9ACL 2026Poster· Natural Language Processing
When T able QA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables
Shenghao Ye · Yu Guo · Dong Jin · Yuxiang Wang · Yikai Shen · Yunpeng Hou · Shuangwu Chen · Jianyang · Xiaofeng Jiang
摘要
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 t...