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cs.CL2026

Cooperative Profiles Predict Multi-Agent LLM Team Performance in AI for Science Workflows

Shivani Kumar, Adarsh Bharathwaj, David Jurgens

Multi-agent systems built from teams of large language models (LLMs) are increasingly deployed for collaborative scientific reasoning and problem-solving. These systems require age…

cs.CL2026

Think Multilingual, Not Harder: A Data-Efficient Framework for Teaching Reasoning Models to Code-Switch

Eleanor M. Lin, David Jurgens

Recent developments in reasoning capabilities have enabled large language models to solve increasingly complex mathematical, symbolic, and logical tasks. Interestingly, while reaso…

cs.CL2025

Unstructured Evidence Attribution for Long Context Query Focused Summarization

Dustin Wright, Zain Muhammad Mujahid, Lu Wang +2

Large language models (LLMs) are capable of generating coherent summaries from very long contexts given a user query, and extracting and citing evidence spans helps improve the tru…

cs.CL2025

One Model, Many Morals: Uncovering Cross-Linguistic Misalignments in Computational Moral Reasoning

Sualeha Farid, Jayden Lin, Zean Chen +2

Large Language Models (LLMs) are increasingly deployed in multilingual and multicultural environments where moral reasoning is essential for generating ethically appropriate respon…

cs.CL2025

Evaluation Framework for AI Systems in "the Wild"

Sarah Jabbour, Trenton Chang, Anindya Das Antar +13

Generative AI (GenAI) models have become vital across industries, yet current evaluation methods have not adapted to their widespread use. Traditional evaluations often rely on ben…

cs.CL2025

Are Rules Meant to be Broken? Understanding Multilingual Moral Reasoning as a Computational Pipeline with UniMoral

Shivani Kumar, David Jurgens

Moral reasoning is a complex cognitive process shaped by individual experiences and cultural contexts and presents unique challenges for computational analysis. While natural langu…