7 papers
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
Generative models have emerged as a promising paradigm for offline multi-agent reinforcement learning (MARL), but existing approaches require many iterative sampling steps. Recent…
One Step Is Enough: Dispersive MeanFlow Policy Optimization
Guowei Zou, Haitao Wang, Hejun Wu +3
Real-time robotic control demands fast action generation. However, existing generative policies based on diffusion and flow matching require multi-step sampling, fundamentally limi…
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…