activity
20242026
most citedAn Eulerian Vortex Method on Flow Maps

13 citations · 26 across the 14 of their papers we have counts for

collaborators

17 papers

cs.CV2026

Recursive Code World Models: Building Complex Worlds through Recursive Scene Programs

Zhiqi Li, Yuxuan Liao, Bo Zhu

Code world models represent worlds as executable programs, but this representation alone does not determine how to construct a complex world. We introduce Recursive Code World Mode…

cs.GR2026

Hamiltonian Two-Way Coupling of Nonlinear Waves and 3D Flows

Sinan Wang, Ruicheng Wang, Taiyuan Zhang +5

Simulating large-scale free-surface water by coupling a localized 3D fluid solver to a cheaper 2D surface model has long faced a mismatch in wave dynamics: efficient 2D wave models…

cs.LG2026

Flow-Map GRPO: Reinforcement Learning for Few-Step Flow-Map Generators via Anchored Stochastic Composition

Zhiqi Li, Wen Zhang, Bo Zhu

Few-step flow-map generators, such as consistency models and MeanFlow, accelerate sampling by directly learning long-range transport maps between noise and data. However, these mod…

cs.LG2026

A Few-Step Generative Model on Cumulative Flow Maps

Zhiqi Li, Duowen Chen, Yuchen Sun +1

We propose a unified, few-step generative modeling framework based on \emph{cumulative flow maps} for long-range transport in probability space, inspired by flow-map techniques for…

cs.GR2026

Generative Modeling with Orbit-Space Particle Flow Matching

Sinan Wang, Jinjin He, Shenyifan Lu +3

We present Orbit-Space Geometric Probability Paths (OGPP), a particle-native flow-matching framework for generative modeling of particle systems. OGPP is motivated by two insights:…

cs.LG2026

Trajectory Consistency for One-Step Generation on Euler Mean Flows

Zhiqi Li, Yuchen Sun, Duowen Chen +2

We propose \emph{Euler Mean Flows (EMF)}, a flow-based generative framework for one-step and few-step generation that enforces long-range trajectory consistency with minimal sampli…