collaborators

16 papers

cs.CL2026

"I Didn't Make the Micro Decisions": Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration

Eunsu Kim, Jessica R. Mindel, Kyungjin Kim +1

As large language models (LLMs) increasingly shape how users form, refine, and extend their goals, attributing contributions in human-AI collaboration becomes critical for users ca…

cs.CL2026

K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts

Nahyun Lee, Dongkeun Yoon, Guijin Son +12

Frontier model evaluations are shifting from foundational capabilities (e.g., instruction following and reasoning) toward compositional, agentic ones, but Korean agentic benchmarks…

cs.CL2026

LoCar: Localization-Aware Evaluation of In-Vehicle Assistants through Fine-Grained Sociolinguistic Control

Seogyeong Jeong, Kiwoong Park, Seyoung Song +4

While Large Language Models (LLMs) are increasingly integrated into in-vehicle conversational systems, identifying the optimal model remains challenging due to the lack of domain-s…

cs.CL2026

Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues

Eunsu Kim, Junyeong Park, Juhyun Oh +5

As LLMs are increasingly deployed in real-world interactions, their social reasoning in interpersonal communication becomes critical. To explore their capabilities, we introduce SC…

cs.CL2026

RoleConflictBench: A Benchmark of Role Conflict Scenarios for Evaluating LLMs' Contextual Sensitivity

Jisu Shin, Hoyun Song, Juhyun Oh +4

People often encounter role conflicts -- social dilemmas where the expectations of multiple roles clash and cannot be simultaneously fulfilled. As large language models (LLMs) incr…

cs.CL2026

BLUCK: A Benchmark Dataset for Bengali Linguistic Understanding and Cultural Knowledge

Daeen Kabir, Minhajur Rahman Chowdhury Mahim, Sheikh Shafayat +4

In this work, we introduce BLUCK, a new dataset designed to measure the performance of Large Language Models (LLMs) in Bengali linguistic understanding and cultural knowledge. Our…