ART-RL learns adaptive diffusion sampling timesteps via continuous-time control and Gaussian actor–critic RL, improving and transferring over hand-designed grids at matched budgets.
Hanyang Zhao, Haoxian Chen, Ji Zhang, David Yao, and Wenpin Tang
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4representative citing papers
A new adjoint matching framework formulates flow model alignment as optimal control, enabling direct regression training and terminal-trajectory truncation for efficiency gains on models like SiT-XL and FLUX.
SSPT turns space-syntax integration metrics into post-training feedback signals that improve public-space dominance and functional hierarchy in AI-generated residential floor plans.
ART reparameterizes diffusion sampling time and uses RL to learn optimal timestep schedules that reduce discretization error and improve generation quality across budgets and datasets.
citing papers explorer
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ART for Diffusion Sampling: Continuous-Time Control and Actor-Critic Learning
ART-RL learns adaptive diffusion sampling timesteps via continuous-time control and Gaussian actor–critic RL, improving and transferring over hand-designed grids at matched budgets.
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Improved techniques for fine-tuning flow models via adjoint matching: a deterministic control pipeline
A new adjoint matching framework formulates flow model alignment as optimal control, enabling direct regression training and terminal-trajectory truncation for efficiency gains on models like SiT-XL and FLUX.
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Space Syntax-guided Post-training for Residential Floor Plan Generation
SSPT turns space-syntax integration metrics into post-training feedback signals that improve public-space dominance and functional hierarchy in AI-generated residential floor plans.
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ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
ART reparameterizes diffusion sampling time and uses RL to learn optimal timestep schedules that reduce discretization error and improve generation quality across budgets and datasets.