collaborators

6 papers

cs.CL2026

ResearchMath-14K: Scaling Research-Level Mathematics via Agents

Guijin Son, Seungyeop Yi, Minju Gwak +3

The frontier of mathematics is defined by problems whose solutions are not yet known, yet it remains unclear whether language models can meaningfully engage with such problems with…

cs.AI2026

Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact Verifiers

Wooseok Seo, Seungju Han, Jaehun Jung +6

Fact verification is essential for ensuring the reliability of LLM applications. In this study, we evaluate 12 pre-trained LLMs and one specialized fact-verifier, including frontie…

cs.LG2025

Representation Bending for Large Language Model Safety

Ashkan Yousefpour, Taeheon Kim, Ryan S. Kwon +7

Large Language Models (LLMs) have emerged as powerful tools, but their inherent safety risks - ranging from harmful content generation to broader societal harms - pose significant…

cs.CL2025

Persona Dynamics: Unveiling the Impact of Personality Traits on Agents in Text-Based Games

Seungwon Lim, Seungbeen Lee, Dongjun Min +1

Artificial agents are increasingly central to complex interactions and decision-making tasks, yet aligning their behaviors with desired human values remains an open challenge. In t…

cs.CL2025

DUSK: Do Not Unlearn Shared Knowledge

Wonje Jeung, Sangyeon Yoon, Hyesoo Hong +4

Large language models (LLMs) are increasingly deployed in real-world applications, raising concerns about the unauthorized use of copyrighted or sensitive data. Machine unlearning…

cs.CL2025

When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research

Guijin Son, Jiwoo Hong, Honglu Fan +8

Recent advances in large language models (LLMs) have fueled the vision of automated scientific discovery, often called AI Co-Scientists. To date, prior work casts these systems as…