{"pk":50105,"title":"M2TQA:A Metacognitive Framework for Multi-Table Question Answering","subtitle":null,"abstract":"A Metacognitive Framework for Multi-Table Question Answering\nProcessing structured data is critical in finance, healthcare, and science. While single-table question answering has advanced, multi-table QA remains challenging due to schema understanding, cross-table reasoning, and complex natural language queries. We propose M2TQA , a novel framework inspired by human cognitive and metacognitive mechanisms. M2TQA integrates metadata extraction, query decomposition, and a metacognitive module to enable interpretable, robust solutions for MTQA. It dynamically simulates human-like reasoning through feedback loops, bridging gaps between natural language understanding and structured data processing. Experiments on four benchmarks show M2TQA outperforms baselines by 94.54% and 33.24% in F1 scores. This work advances MTQA and highlights metacognition's role in AI, fostering interdisciplinary connections between cognitive science and artificial intelligence.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Artificial Intelligence; Cognitive Neuroscience; Cognitive architectures; Problem Solving; Agent-based Modeling"}],"section":"Abstracts with Poster Presentation (accepted as Abstracts)","is_remote":true,"remote_url":"https://escholarship.org/uc/item/3gg5v1zh","frozenauthors":[{"first_name":"Jinlong","middle_name":"","last_name":"Tian","name_suffix":"","institution":"National University of Defense Technology","department":""},{"first_name":"Yuhua","middle_name":"","last_name":"Tang","name_suffix":"","institution":"National University of Defense Technology","department":""},{"first_name":"Kejia","middle_name":"","last_name":"Wan","name_suffix":"","institution":"National University of Defense Technology","department":""},{"first_name":"Hao","middle_name":"","last_name":"Tang","name_suffix":"","institution":"National University of Defense Technology","department":""},{"first_name":"Qiyuan","middle_name":"","last_name":"Zhang","name_suffix":"","institution":"National University of Defense Technology","department":""},{"first_name":"Yanfang","middle_name":"","last_name":"Zhou","name_suffix":"","institution":"Academy of Military Sciences","department":""},{"first_name":"Mengmeng","middle_name":"","last_name":"Li","name_suffix":"","institution":"Academy of Military Sciences","department":""},{"first_name":"Xianglong","middle_name":"","last_name":"Li","name_suffix":"","institution":"Academy of Military Sciences","department":""},{"first_name":"Xinhai","middle_name":"","last_name":"Xu","name_suffix":"","institution":"Academy of Military Sciences","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2025-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/50105/galley/38067/download/"}]}