2025
Reinventing Multi-Agent Collaboration through Gaussian-Image Synergy in Diffusion Policies
Ziye Wang*, Li Kang*, Yiran Qin*, Jiahua Ma, Zhanglin Peng, Lei Bai, Ruimao Zhang# (* equal contribution, # corresponding author)
NeurIPS 2025
TL;DR: 3D Gaussians make multi-agent teamwork click.
Reinventing Multi-Agent Collaboration through Gaussian-Image Synergy in Diffusion Policies
Ziye Wang*, Li Kang*, Yiran Qin*, Jiahua Ma, Zhanglin Peng, Lei Bai, Ruimao Zhang# (* equal contribution, # corresponding author)
NeurIPS 2025
TL;DR: 3D Gaussians make multi-agent teamwork click.
VIKI‑R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning
Li Kang*, Xiufeng Song*, Heng Zhou*, Yiran Qin#, Jie Yang, Xiaohong Liu, Philip Torr, Lei Bai#, Zhenfei Yin# (* equal contribution, # corresponding author)
NeurIPS 2025
TL;DR: Boost VLM’s visual reasoning with GRPO to orchestrate collaboration among heterogeneous embodied robots.
VIKI‑R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning
Li Kang*, Xiufeng Song*, Heng Zhou*, Yiran Qin#, Jie Yang, Xiaohong Liu, Philip Torr, Lei Bai#, Zhenfei Yin# (* equal contribution, # corresponding author)
NeurIPS 2025
TL;DR: Boost VLM’s visual reasoning with GRPO to orchestrate collaboration among heterogeneous embodied robots.
RoboFactory: Exploring Embodied Agent Collaboration with Compositional Constraints
Yiran Qin*, Li Kang*, Xiufeng Song*, Zhenfei Yin#, Xiaohong Liu, Xihui Liu, Ruimao Zhang#, Lei Bai# (* equal contribution, # corresponding author)
ICCV 2025 & Best Paper Award at CVPR 2025 MEIS Workshop
TL;DR: Using compositional constraints to coordinate multiple robotic arms for complex—and surprisingly fun—manipulation tasks!
RoboFactory: Exploring Embodied Agent Collaboration with Compositional Constraints
Yiran Qin*, Li Kang*, Xiufeng Song*, Zhenfei Yin#, Xiaohong Liu, Xihui Liu, Ruimao Zhang#, Lei Bai# (* equal contribution, # corresponding author)
ICCV 2025 & Best Paper Award at CVPR 2025 MEIS Workshop
TL;DR: Using compositional constraints to coordinate multiple robotic arms for complex—and surprisingly fun—manipulation tasks!
ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks
Heng Zhou*, Hejia Geng*, Xiangyuan Xue, Li Kang, Yiran Qin, Zhiyong Wang, Zhenfei Yin#, Lei Bai# (* equal contribution, # corresponding author)
EMNLP 2025 Main
TL;DR: A reward-driven multi-agent system that self-organizes to enable efficient collaboration through dynamic optimization and agent selection.
ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks
Heng Zhou*, Hejia Geng*, Xiangyuan Xue, Li Kang, Yiran Qin, Zhiyong Wang, Zhenfei Yin#, Lei Bai# (* equal contribution, # corresponding author)
EMNLP 2025 Main
TL;DR: A reward-driven multi-agent system that self-organizes to enable efficient collaboration through dynamic optimization and agent selection.
2024
Adaptive Selecting Algorithm For Runtime Types of Microservices
Li Kang*, Binbin Feng*, Zhijun Ding# (* equal contribution, # corresponding author)
ICWS 2024
TL;DR: Adaptively select optimal runtimes (serverless/serverful) for microservices to enhance performance and cost efficiency.
Adaptive Selecting Algorithm For Runtime Types of Microservices
Li Kang*, Binbin Feng*, Zhijun Ding# (* equal contribution, # corresponding author)
ICWS 2024
TL;DR: Adaptively select optimal runtimes (serverless/serverful) for microservices to enhance performance and cost efficiency.