4 citations · 4 across the 8 of their papers we have counts for
10 papers
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…
Human-AI Co-Creativity: Advances, Opportunities, and Challenges
Adish Singla, Abhilasha Ravichander, Liwei Jiang +7
This survey article has grown out of the human-AI co-creativity workshop organized by the authors at the ICML 2026 conference. We organized this workshop as part of a community-bui…
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…
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…
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…
World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models
Eunsu Kim, Junyeong Park, Na Min An +9
In a globalized world, cultural elements from diverse origins frequently appear together within a single visual scene. We refer to these as culture mixing scenarios, yet how Large…
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…
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…
When Tom Eats Kimchi: Evaluating Cultural Bias of Multimodal Large Language Models in Cultural Mixture Contexts
Jun Seong Kim, Kyaw Ye Thu, Javad Ismayilzada +6
In a highly globalized world, it is important for multi-modal large language models (MLLMs) to recognize and respond correctly to mixed-cultural inputs. For example, a model should…
LLM-C3MOD: A Human-LLM Collaborative System for Cross-Cultural Hate Speech Moderation
Junyeong Park, Seogyeong Jeong, Seyoung Song +2
Content moderation is a global challenge, yet major tech platforms prioritize high-resource languages, leaving low-resource languages with scarce native moderators. Since effective…