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Marine Carpuat

ACL 2026×4评测与基准社会与人本多语言与语言学检索与知识多模态
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0 一作 · 4 篇 · ACL 2026

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2026 顶会论文

4
作者位次 #4/4ACL 2026Poster· Natural Language Processing

Measuring User’s Mental Models of Speech Translation in Human- AI Collaboration

HyoJung Han · Nishant Balepur · Jordan Lee Boyd-Graber · Marine Carpuat

摘要

Millions of people use machine translation (MT) tools daily, yet little is known about their perception of what systems can and cannot do. This paper studies users’ mental models of speech translation systems through a new framework based on cross-lingual question answering, where users either ac...

检索与知识多语言与语言学多模态OpenReview 项目页
作者位次 #5/6ACL 2026Poster· Natural Language Processing

Can You Make It Sound Like You? Post-Editing LLM -Generated Text for Personal Style

Connor Baumler · Calvin Bao · Huy Nghiem · Xinchen Yang · Marine Carpuat · Hal Daumé Iii

摘要

Despite the growing use of large language models (LLMs) for writing tasks, users may hesitate to rely on LLMs when personal style is important. Post-editing LLM-generated drafts or translations is a common collaborative writing strategy, but it remains unclear whether users can effectively reshap...

评测与基准多语言与语言学社会与人本OpenReview 项目页
作者位次 #5/6ACL 2026Findings· Findings of ACL

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms

Dayeon Ki · Yu Hou · Rachel Rudinger · Hal Daumé Iii · Marine Carpuat · Fumeng Yang

摘要

Neologisms and emerging slang are central to daily conversation, yet challenging for non-native speakers (NNS) to interpret and use appropriately in cross-cultural communication with native speakers (NS). NNS increasingly make use of Artificial Intelligence (AI) tools to learn these words. We stu...

评测与基准社会与人本可解释性OpenReview 项目页
作者位次 #3/4ACL 2026Findings· Findings of ACL

Take Out Your Calculators: Estimating the Real Difficulty of Question Items with LLM Student Simulations

Christabel Acquaye · Yi Ting Huang · Marine Carpuat · Rachel Rudinger

摘要

Standardized math assessments require expensive human pilot studies to establish the difficulty of test items. We investigate the predictive value of open-source large language models (LLMs) for evaluating the difficulty of multiple-choice math questions for real-world students. We show that, whi...

社会与人本评测与基准推理OpenReview 项目页

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