Papers by Kyumin Kim

2 papers
Piece of Table: A Divide-and-Conquer Approach for Selecting Subtables in Table Question Answering (2026.acl-long)

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Challenge: Existing approaches to QA tables rely on independent row or column selection, fail to capture cross-row and cross-column dependencies, or attempt global reasoning.
Approach: They propose a divide-and-conquer subtable selection framework that aggregates local evidence without requiring explicit global reasoning.
Outcome: The proposed framework outperforms previous approaches to table QA in the noisy context.
SSMix: Saliency-Based Span Mixup for Text Classification (2021.findings-acl)

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Challenge: SSMix synthesizes a sentence while preserving the locality of two original texts by span-based mixing and keeping more tokens related to the prediction relying on saliency information.
Approach: They propose a new method where the operation is performed on input text rather than on hidden vectors like previous approaches.
Outcome: The proposed method outperforms hidden-level mixup methods on a wide range of text classification benchmarks including textual entailment, sentiment classification, and questiontype classification.

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