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cs.LG2026
Integration Matters: Rollout-Based Training for Constrained Diffusion Models
Xiaoxuan Liang, Saeid Naderiparizi, Berend Zwartsenberg +1
Constrained generative models aim to produce samples that satisfy complex feasibility constraints while remaining faithful to the data distribution. Existing constrained generation…
cs.LG2026
Improved Constrained Generation by Bridging Pretrained Generative Models
Xiaoxuan Liang, Saeid Naderiparizi, Yunpeng Liu +2
Constrained generative modeling is fundamental to applications such as robotic control and autonomous driving, where models must respect physical laws and safety-critical constrain…