1 citations · 1 across the 2 of their papers we have counts for
6 papers
Advances and Innovations in the Multi-Agent Robotic System (MARS) Challenge
Li Kang, Heng Zhou, Xiufeng Song +41
Recent advancements in multimodal large language models and vision-languageaction models have significantly driven progress in Embodied AI. As the field transitions toward more com…
GauDP: Reinventing Multi-Agent Collaboration through Gaussian-Image Synergy in Diffusion Policies
Ziye Wang, Li Kang, Yiran Qin +4
Recently, effective coordination in embodied multi-agent systems has remained a fundamental challenge, particularly in scenarios where agents must balance individual perspectives w…
SSRL: Self-Search Reinforcement Learning
Yuchen Fan, Kaiyan Zhang, Heng Zhou +15
We investigate the potential of large language models (LLMs) to serve as efficient simulators for agentic search tasks in reinforcement learning (RL), thereby reducing dependence o…
VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning
Li Kang, Xiufeng Song, Heng Zhou +6
Coordinating multiple embodied agents in dynamic environments remains a core challenge in artificial intelligence, requiring both perception-driven reasoning and scalable cooperati…
RoboFactory: Exploring Embodied Agent Collaboration with Compositional Constraints
Yiran Qin, Li Kang, Xiufeng Song +5
Designing effective embodied multi-agent systems is critical for solving complex real-world tasks across domains. Due to the complexity of multi-agent embodied systems, existing me…
ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks
Heng Zhou, Hejia Geng, Xiangyuan Xue +5
Multi-agent systems (MAS) have emerged as a promising approach for enhancing the reasoning capabilities of large language models in complex problem-solving; however, current MAS fr…