Piece of Table: A Divide-and-Conquer Approach for Selecting Subtables in Table Question Answering
Wonjin Lee Pohang University of Science and Technology, Kyumin Kim LG CNS, Sungjae Lee, Jihun Lee Pohang University of Science and Technology, Kwang In Kim Pohang University of Science and Technology
Applying language models (LMs) to tables is challenging due to the mismatch between the two-dimensional structure of tables and the one-dimensional inputs expected by LMs. This mismatch forces linearization, making LMs particularly sensitive to irrelevant cells. Subtable selection mitigates this challenge by isolating question-relevant content prior to answer generation. However, existing approaches either rely on independent row or column selection, failing to capture cross-row and cross-column dependencies, or attempt global reasoning and face challenges similar to holistic table QA under noisy contexts. We propose PieTa (Piece of Table), a divide-and-conquer subtable selection framework that progressively aggregates locally selected evidence without requiring explicit global reasoning. PieTa uses an iterative, window-based multi-resolution process to construct compact subtables that capture global dependencies while limiting LM exposure to irrelevant content. Extensive experiments demonstrate that PieTa consistently outperforms prior subtable-based and holistic table QA approaches.
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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2026 · 正式发表