Papers by Daiki Matsuoka

2 papers
Analysis of the Neglect-Zero Effect in Large Language Models (2026.acl-srw)

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Challenge: a neglect-zero effect is a human cognitive bias in language processing . it is unclear whether LLMs also exhibit this effect .
Approach: They focus on a human cognitive bias called the *neglect-zero effect* . they propose a paradigm where exposure to a preceding sentence facilitates processing of a subsequent sentence due to their similarity.
Outcome: The proposed paradigm based on priming facilitates processing of a subsequent sentence due to their similarity to the target.
Evaluating Structural Generalization in Neural Machine Translation (2024.findings-acl)

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Challenge: Existing studies have focused on compositional generalization with semantic parsing, but it remains unclear to what extent models can translate sentences that require structural generalization.
Approach: They construct a machine translation dataset that measures compositional generalization with control of words and sentence structures.
Outcome: The proposed model struggle more in structural generalization than in compositional generalization.

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