collaborators

6 papers

cs.CL2026

EMBGuard: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents

Dongwook Choi, Taeyoon Kwon, Bogyung Jeong +6

MLLM-powered embodied agents deployed in real-world environments encounter physical hazards. However, existing approaches lack explicit mechanisms for identifying hazards and reaso…

cs.AI2026

Towards Direct Evaluation of Harness Optimizers via Priority Ranking

Kai Tzu-iunn Ong, Minseok Kang, Dongwook Choi +9

Harness optimization enables automated agent creation by having an optimizer agent iteratively update the harness of target agents. Despite its success, current studies evaluate op…

cs.AI2026

PAC-BENCH: Evaluating Multi-Agent Collaboration under Privacy Constraints

Minjun Park, Donghyun Kim, Hyeonjong Ju +5

We are entering an era in which individuals and organizations increasingly deploy dedicated AI agents that interact and collaborate with other agents. However, the dynamics of mult…

cs.CL2026

Embodied Agents Meet Personalization: Investigating Challenges and Solutions Through the Lens of Memory Utilization

Taeyoon Kwon, Dongwook Choi, Hyojun Kim +5

LLM-powered embodied agents have shown success on conventional object-rearrangement tasks, but providing personalized assistance that leverages user-specific knowledge from past in…

cs.CL2025

Web-Shepherd: Advancing PRMs for Reinforcing Web Agents

Hyungjoo Chae, Sunghwan Kim, Junhee Cho +18

Web navigation is a unique domain that can automate many repetitive real-life tasks and is challenging as it requires long-horizon sequential decision making beyond typical multimo…

cs.AI2025

Designing Memory-Augmented AR Agents for Spatiotemporal Reasoning in Personalized Task Assistance

Dongwook Choi, Taeyoon Kwon, Dongil Yang +2

Augmented Reality (AR) systems are increasingly integrating foundation models, such as Multimodal Large Language Models (MLLMs), to provide more context-aware and adaptive user exp…