collaborators

9 papers

cs.CL2026

Not What, But How: A Framework for Auditing LLM Responses across Positioning, Generalization, Anthropomorphism, and Maxims

Siddhesh Milind Pawar, Sarah Masud, Haneul Yoo +2

Large language models (LLMs) are being increasingly used to answer subjective, information-seeking questions, where users are sensitive to how responses are communicated, not just…

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

Can Large Language Models Understand, Reason About, and Generate Code-Switched Text?

Genta Indra Winata, David Anugraha, Patrick Amadeus Irawan +15

Code-switching is a pervasive phenomenon in multilingual communication, yet the robustness of large language models (LLMs) in mixed-language settings remains insufficiently underst…

cs.CL2026

From National Curricula to Cultural Awareness: Constructing Open-Ended Culture-Specific Question Answering Dataset

Haneul Yoo, Won Ik Cho, Geunhye Kim +1

Large language models (LLMs) achieve strong performance on many tasks, but their progress remains uneven across languages and cultures, often reflecting values latent in English-ce…

cs.CL2026

OLA: Output Language Alignment in Code-Switched LLM Interactions

Juhyun Oh, Haneul Yoo, Faiz Ghifari Haznitrama +1

Code-switching, alternating between languages within a conversation, is natural for multilingual users, yet poses fundamental challenges for large language models (LLMs). When a us…

cs.CL2025

Gradual Code-Switching as Inference-Time Cross-Lingual Representational Alignment for LLMs

Haneul Yoo, Jiho Jin, Kyunghyun Cho +1

While large language models (LLMs) have achieved notable progress in multilingual settings, their performance remains uneven across languages as LLMs often rely on English-centric…