7 papers · 1 filter
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…
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…
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…
Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversation
Dongjin Kang, Sunghwan Kim, Taeyoon Kwon +5
Emotional Support Conversation (ESC) is a task aimed at alleviating individuals' emotional distress through daily conversation. Given its inherent complexity and non-intuitive natu…
Towards Lifelong Dialogue Agents via Timeline-based Memory Management
Kai Tzu-iunn Ong, Namyoung Kim, Minju Gwak +6
To achieve lifelong human-agent interaction, dialogue agents need to constantly memorize perceived information and properly retrieve it for response generation (RG). While prior st…
Coffee-Gym: An Environment for Evaluating and Improving Natural Language Feedback on Erroneous Code
Hyungjoo Chae, Taeyoon Kwon, Seungjun Moon +7
This paper presents Coffee-Gym, a comprehensive RL environment for training models that provide feedback on code editing. Coffee-Gym includes two major components: (1) Coffee, a da…