1 citations · 1 across the 6 of their papers we have counts for
9 papers
A Modern System Recipe for Situated Embodied Human-Robot Conversation with Real-Time Multimodal LLMs and Tool-Calling
Dong Won Lee, Sarah Gillet, Louis-Philippe Morency +2
Situated embodied conversation requires robots to interleave real-time dialogue with active perception: deciding what to look at, when to look, and what to say under tight latency…
Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning
Zhiyuan Hu, Yunhai Hu, Juncheng Liu +9
Multi-agent systems have evolved into practical LLM-driven collaborators for many applications, gaining robustness from diversity and cross-checking. However, multi-agent RL (MARL)…
Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs
Zhiyuan Hu, Yucheng Wang, Yufei He +7
Reinforcement learning (RL) has become a central paradigm for post-training large language models (LLMs), particularly for complex reasoning tasks, yet it often suffers from explor…
Tiered Agentic Oversight: A Hierarchical Multi-Agent System for Healthcare Safety
Yubin Kim, Hyewon Jeong, Chanwoo Park +9
Large language models (LLMs) deployed as agents introduce significant safety risks in clinical settings due to their potential for error and single points of failure. We introduce…
BehaviorSFT: Behavioral Token Conditioning for Clinical Agents Across the Proactivity Spectrum
Yubin Kim, Zhiyuan Hu, Hyewon Jeong +11
Large Language Models (LLMs) as clinical agents require careful behavioral adaptation. While adept at reactive tasks (e.g., diagnosis reasoning), LLMs often struggle with proactive…
VocalAgent: Large Language Models for Vocal Health Diagnostics with Safety-Aware Evaluation
Yubin Kim, Taehan Kim, Wonjune Kang +8
Vocal health plays a crucial role in peoples' lives, significantly impacting their communicative abilities and interactions. However, despite the global prevalence of voice disorde…