most citedLLM-C3MOD: A Human-LLM Collaborative System for Cross-Cultural Hate Speech Moderation

4 citations · 4 across the 8 of their papers we have counts for

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cs.CL2026

The Role of Fine-grained Harm Signals in LLM Safety

Soyeon Park, Seogyeong Jeong, Sunwoo Kim +1

Prior work has shown that internal harmfulness representations in large language models vary across risk categories, while sharing a common general harm representation component. T…

cs.CL2026

Beneath the Surface of Chains-of-Thought: A Mechanistic Interpretation of Reasoning Operations in LLMs

Seogyeong Jeong, Jaehui Hwang, Dongyoon Han +3

Reasoning in large language models unfolds through diverse functional operations, such as problem formulation, goal decomposition, and deduction. Although these operations are expl…

cs.CL2026

JuICE: A Benchmark for Evaluating LLM-Judge in Identifying Cultural Errors

Jiho Jin, Junho Myung, Juhyun Oh +5

As large language models (LLMs) are increasingly deployed to users around the world, they are integrated into everyday tasks across diverse cultural contexts, from drafting persona…

cs.CL2026

Investigating Counterfactual Unfairness in LLMs towards Identities through Humor

Shubin Kim, Yejin Son, Junyeong Park +6

Humor holds up a mirror to social perception: what we find funny often reflects who we are and how we judge others. When language models engage with humor, their reactions expose t…

cs.CL2025

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.CL2025

MUG-Eval: A Proxy Evaluation Framework for Multilingual Generation Capabilities in Any Language

Seyoung Song, Seogyeong Jeong, Eunsu Kim +4

Evaluating text generation capabilities of large language models (LLMs) is challenging, particularly for low-resource languages where methods for direct assessment are scarce. We p…