11 papers
MA-FPPO: Multi-Agent Flow-Pretrained Policy Optimization
Guowei Zou, Haonan Chen, Haitao Wang +3
Multi-agent flow policies learn cooperative behavior from fixed offline datasets, but often struggle to complete tasks in situations not covered by the offline data. In these situa…
G2MAF: Test-Time Gradient Guidance for Multi-Agent Flow Policies
Guowei Zou, Haitao Wang, Guoxin Wang +4
Offline multi-agent reinforcement learning (MARL) learns cooperative policies from fixed datasets without further environment interaction and a learned policy is frozen at deployme…
MA-WAM: Multi-Agent World-Action Model for Test-Time Planning
Guowei Zou, Haitao Wang, Guoxin Wang +4
Multi-agent cooperative tasks require different agents to execute a joint action simultaneously, and each agent's action affects both the observations and responses of the other ag…
Distilling LLM Reasoning into an Interpretable Policy Tree for Human-AI Collaboration
Beiwen Zhang, Yongheng Liang, Guowei Zou +2
Constructing efficient and reliable policies to assist humans is indispensable for human-AI collaboration. Existing methods mainly follow two lines of work. Most prior work relies…
Med-DisSeg: Dispersion-Driven Representation Learning for Fine-Grained Medical Image Segmentation
Zhiquan Chen, Haitao Wang, Guowei Zou +1
Accurate medical image segmentation is fundamental to precision medicine, yet robust delineation remains challenging under heterogeneous appearances, ambiguous boundaries, and larg…
SpectraFlow: Unifying Structural Pretraining and Frequency Adaptation for Medical Image Segmentation
Zhiquan Chen, Haitao Wang, Guowei Zou +1
Medical image segmentation remains challenging in low-data regimes, where scarce annotations often yield poor generalization and ambiguous boundaries with missing fine structures.…
CoFlow: Coordinated Few-Step Flow for Offline Multi-Agent Decision Making
Guowei Zou, Haitao Wang, Beiwen Zhang +2
How can generative offline multi-agent reinforcement learning achieve both fast joint trajectory generation and effective cooperation? Multi-agent diffusion models generate joint t…
OGPO: One-Step Generative Policy Optimization for Real-Time Robot Control
Guowei Zou, Haitao Wang, Hejun Wu +3
Real-time robot control demands fast action generation. Diffusion and flow matching policies for robot control require multi-step sampling, limiting their deployment in real-time s…
DM1: MeanFlow with Dispersive Regularization for 1-Step Robotic Manipulation
Guowei Zou, Haitao Wang, Hejun Wu +3
The ability to learn multi-modal action distributions is indispensable for robotic manipulation policies to perform precise and robust control. Flow-based generative models have re…
PACT: Phenotype-Aware Contrastive Team Representation for Multi-Phenotype Grouped Ad Hoc Teamwork
Beiwen Zhang, Yongheng Liang, Guowei Zou +3
Learning to collaborate with various unfamiliar teammates poses a great challenge in the domain of multi-agent systems. Existing ad hoc teamwork methods typically drive controlled…
D2PPO: Diffusion Policy Policy Optimization with Dispersive Loss
Guowei Zou, Weibing Li, Hejun Wu +3
Diffusion policies excel at robotic manipulation by naturally modeling multimodal action distributions in high-dimensional spaces. Nevertheless, diffusion policies suffer from diff…