collaborators

5 papers

cs.LG2026

MobileSafetyBench: Evaluating Safety of Autonomous Agents in Mobile Device Control

Juyong Lee, Dongyoon Hahm, June Suk Choi +2

Autonomous agents powered by large language models (LLMs) show promising potential in assistive tasks across various domains, including mobile device control. As these agents inter…

cs.CL2025

Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents

Dongjun Lee, Juyong Lee, Kyuyoung Kim +4

Recent advances in large language models (LLMs) have led to a growing interest in developing LLM-based agents for automating web tasks. However, these agents often struggle with ev…

cs.AI2025

Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation

Sayash Kapoor, Benedikt Stroebl, Peter Kirgis +28

AI agents have been developed for complex real-world tasks from coding to customer service. But AI agent evaluations suffer from many challenges that undermine our understanding of…

cs.HC2025

Benchmarking Mobile Device Control Agents across Diverse Configurations

Juyong Lee, Taywon Min, Minyong An +4

Mobile device control agents can largely enhance user interactions and productivity by automating daily tasks. However, despite growing interest in developing practical agents, the…

cs.AI2025

Automated Skill Discovery for Language Agents through Exploration and Iterative Feedback

Yongjin Yang, Sinjae Kang, Juyong Lee +3

Training large language model (LLM) agents to acquire necessary skills and perform diverse tasks within an environment is gaining interest as a means to enable open-endedness. Howe…