3 papers
cs.LG2026
Riemannian MeanFlow for One-Step Generation on Manifolds
Zichen Zhong, Haoliang Sun, Yukun Zhao +2
Flow Matching enables simulation-free training of generative models on Riemannian manifolds, yet sampling typically still relies on numerically integrating a probability-flow ODE.…
cs.CV2026
Seek-and-Solve: Benchmarking MLLMs for Visual Clue-Driven Reasoning in Daily Scenarios
Xiaomin Li, Tala Wang, Zichen Zhong +7
Daily scenarios are characterized by visual richness, requiring Multimodal Large Language Models (MLLMs) to filter noise and identify decisive visual clues for accurate reasoning.…
cs.CV2026
EFF-Grasp: Energy-Field Flow Matching for Physics-Aware Dexterous Grasp Generation
Yukun Zhao, Zichen Zhong, Yongshun Gong +2
Denoising generative models have recently become the dominant paradigm for dexterous grasp generation, owing to their ability to model complex grasp distributions from large-scale…