Marine Carpuat
Associate Professor · University of Maryland
Department of Computer Science & UMIACS
Director, CLIP Lab · Member, TRAILS & AIM
I develop multilingual AI systems to help people communicate across languages, and study whether they actually succeed.
Research
When AI mediates communication across languages and cultures, does it genuinely help people understand one another? Or does it just appear to?
Across settings, we observe a gap between surface-level performance and real communicative success. Understanding and addressing this gap is the core focus of my research.
My group approaches this problem from multiple angles: from the internal representations that enable or undermine multilingual capabilities in large language models, to how real people perceive, rely on, and are sometimes misled by AI-mediated communication. We develop new techniques and evaluation methods, and complement this technical work with human-centered and interdisciplinary studies.
Current directions
Right now, my group is most excited about three directions: designing evaluation frameworks for AI-mediated communication that connect empirical findings to technology development; understanding and improving generalization across languages while preserving cultural alignment; and pushing multilingual AI beyond text to the full range of modalities that real communication requires.
Selected Papers
Recent work spanning user perception and reliance on machine translation, quality signals for text and speech, and generalization in multilingual LLMs. Full list on Google Scholar →
Bio · Short bio for talks and panels
Marine Carpuat is an Associate Professor in the Department of Computer Science at the University of Maryland, where she is also a member of UMIACS and director of the CLIP Lab. Her research focuses on developing AI techniques that help people communicate across languages, and studying whether those systems actually succeed. Her work spans foundational NLP methods, evaluation methodology, and human-centered studies of how people perceive and rely on AI-generated translations. She has published extensively at venues including ACL, EMNLP, NAACL, and CHI, and has received paper awards from *SEM, TALN, and EMNLP. She served as Program Co-Chair of NAACL 2022. Before joining UMD, she was a Research Officer at the National Research Council Canada. She received her PhD from the Hong Kong University of Science and Technology and a diplôme d'ingénieur from the French grande école Supélec.
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