3 papers
cs.AI2026
Improved techniques for fine-tuning flow models via adjoint matching: a deterministic control pipeline
Zhengyi Guo, Jiayuan Sheng, David D. Yao +1
We propose a deterministic adjoint matching framework that formulates human preference alignment for flow-based generative models as an optimal control problem over velocity fields…
cs.AI2026
Conditional Diffusion Guidance under Hard Constraint: A Stochastic Analysis Approach
Zhengyi Guo, Wenpin Tang, Renyuan Xu
We study conditional generation in diffusion models under hard constraints, where generated samples must satisfy prescribed events with probability one. Such constraints arise natu…
stat.ML2025
Diffusion Generative Models Meet Compressed Sensing, with Applications to Imaging and Finance
Zhengyi Guo, Jiatu Li, Wenpin Tang +1
In this study we develop dimension-reduction techniques to accelerate diffusion model inference in the context of synthetic data generation. The idea is to integrate compressed sen…