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Saptarshi Ghosh

ACL 2026×3评测与基准数据与预训练代码对齐与偏好可解释性
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2 一作 · 3 篇 · ACL 2026

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2026 顶会论文

3
作者位次 #2/3ACL 2026Poster· Natural Language Processing

Evaluating the Impact of Verbal Multiword Expressions on Machine Translation

Linfeng Liu · Saptarshi Ghosh · Tianyu Jiang

摘要

Verbal multiword expressions (VMWEs) remain difficult for machine translation because their meanings are often not recoverable from their component words. In this study, we analyze the impact of three VMWE categories—verbal idioms, verb-particle constructions, and light verb constructions—on mach...

评测与基准数据与预训练代码OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

M et F use: Figurative Fusion between Metonymy and Metaphor

Saptarshi Ghosh · Tianyu Jiang

摘要

Metonymy and metaphor often co-occur in natural language, yet computational work has studied them largely in isolation. We introduce a framework that transforms a literal sentence into three figurative variants: metonymic, metaphoric, and hybrid. Using this framework, we construct MetFuse, the fi...

对齐与偏好评测与基准数据与预训练OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

Exploring Concreteness Through a Figurative Lens

Saptarshi Ghosh · Tianyu Jiang

摘要

Static concreteness ratings are widely used in NLP, yet a word’s concreteness can shift with context, especially in figurative language such as metaphor, where common concrete nouns can take abstract interpretations. While such shifts are evident from context, it remains unclear how LLMs understa...

可解释性效率与系统OpenReview 项目页

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