Papers by Bai Qirui

1 papers
Rethinking Table Pruning in TableQA: From Sequential Revisions to Gold Trajectory-Supervised Parallel Search (2026.acl-long)

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Challenge: Existing pruning methods rely on sequential revisions and unreliable critique signals . Existing methods fail to detect the loss of answer-critical data .
Approach: They propose a table pruning framework which transforms table pruning to gold trajectory-supervised parallel search.
Outcome: The proposed framework outperforms the strongest baseline pruning framework by 3.2% on various tabular reasoning tasks.

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