Papers by Shengxin Liu

1 papers
DeReA: Improving Idiom Translation with Detect-Retrieve-Arbitrate Reasoning (2026.acl-long)

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Challenge: Existing approaches to idiom translation are limited by the constraints of static parametric memory and retrieval noise . idiomatic expressions are non-compositional units where figurative meanings diverge from literal interpretations .
Approach: They propose a detect-retrieve-arbitrate framework that detects idiomatic spans by reasoning over semantic conflicts between literal and contextual meanings.
Outcome: The proposed framework improves GPT-5-mini and Emerging Slang datasets on various model scales.

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