7 citations · 8 across the 10 of their papers we have counts for
7 papers · 1 filter
Unlocking Structured Pruning for Reasoning Language Models via Attention-Preserving MLP Trimming
Woosang Lim, Haneul Yoo, Vincent-Daniel Yun +1
Structured pruning reduces LLM inference costs by removing model components to produce smaller dense models. However, existing methods can cause reasoning performance to collapse o…
Prefill-Free Cross-Family KV Cache Transfer for Heterogeneous Multi-Agent LLMs
Vincent-Daniel Yun, Woosang Lim, Haneul Yoo +3
Recent multi-agent LLM systems increasingly combine heterogeneous models for specialized agent roles. However, text-based communication requires each receiver to prefill shared con…
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…
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…
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…
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…
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…