Diffusion models exhibit a structural limitation when generating samples on low-dimensional feasible regions for constrained tasks, and sequential autoregressive generation using RL and MCTS improves constraint satisfaction.
Clipdraw: Exploring text-to-drawing synthesis through language-image encoders.Advances in Neural Information Processing Sys- tems, 35:5207–5218, 2022
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When Diffusion Breaks Constraints: Sequential Autoregressive Generation with RL and MCTS
Diffusion models exhibit a structural limitation when generating samples on low-dimensional feasible regions for constrained tasks, and sequential autoregressive generation using RL and MCTS improves constraint satisfaction.