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20242026
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cs.CL2026

AdaMame: A Training Recipe for Adaptive Multilingual Reasoning

Dayeon Ki, Kevin Duh, Marine Carpuat

While Large Reasoning Models (LRMs) show strong performance in English, they often fail to reason in the language of the query, a phenomenon known as language collapse. Existing RL…

cs.CL2026

Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG

Dayeon Ki, Marine Carpuat, Paul McNamee +4

Multilingual Retrieval-Augmented Generation (mRAG) systems enable language models to answer knowledge-intensive queries with citation-supported responses across languages. Despite…

cs.CL2026

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

Dayeon Ki, Yu Hou, Rachel Rudinger +3

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 wi…

cs.CL2026

What Makes Good Multilingual Reasoning? Disentangling Reasoning Traces with Measurable Features

Dayeon Ki, Kevin Duh, Marine Carpuat

Large Reasoning Models (LRMs) still exhibit large performance gaps between English and other languages, yet much current work assumes these gaps can be closed simply by making reas…

cs.CL2026

Pragmatics Meets Culture: Culturally-adapted Artwork Description Generation and Evaluation

Lingjun Zhao, Dayeon Ki, Marine Carpuat +1

Language models are known to exhibit various forms of cultural bias in decision-making tasks, yet much less is known about their degree of cultural familiarity in open-ended text g…

cs.CL2025

Can They Dixit? Yes they Can! Dixit as a Playground for Multimodal Language Model Capabilities

Nishant Balepur, Dang Nguyen, Dayeon Ki

Multi-modal large language models (MLMs) are often assessed on static, individual benchmarks -- which cannot jointly assess MLM capabilities in a single task -- or rely on human or…