collaborators

5 papers

cs.AI2026

COMPASS: A Framework for Evaluating Organization-Specific Policy Alignment in LLMs

Dasol Choi, DongGeon Lee, Brigitta Jesica Kartono +6

As large language models are deployed in high-stakes enterprise applications, from healthcare to finance, ensuring adherence to organization-specific policies has become essential.…

cs.CL2026

EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes

Kyunghoon Bae, Eunbi Choi, Kibong Choi +37

This technical report introduces EXAONE 4.0, which integrates a Non-reasoning mode and a Reasoning mode to achieve both the excellent usability of EXAONE 3.5 and the advanced reaso…

cs.CL2025

Are Vision-Language Models Safe in the Wild? A Meme-Based Benchmark Study

DongGeon Lee, Joonwon Jang, Jihae Jeong +1

Rapid deployment of vision-language models (VLMs) magnifies safety risks, yet most evaluations rely on artificial images. This study asks: How safe are current VLMs when confronted…

cs.CL2025

Verbosity-Aware Rationale Reduction: Effective Reduction of Redundant Rationale via Principled Criteria

Joonwon Jang, Jaehee Kim, Wonbin Kweon +2

Large Language Models (LLMs) rely on generating extensive intermediate reasoning units (e.g., tokens, sentences) to enhance final answer quality across a wide range of complex task…

cs.SE2025

How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code

Seonghyeon Lee, Heejae Chon, Joonwon Jang +2

Language models (LMs) have exhibited impressive abilities in generating code from natural language requirements. In this work, we highlight the diversity of code generated by LMs a…