AI RESEARCH
Consistency Regularised Gradient Flows for Inverse Problems
arXiv CS.LG
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ArXi:2605.07907v1 Announce Type: cross Vision-Language Latent Diffusion Models (LDMs) (Rombach, 2022) provide powerful generative priors for inverse problems. However, existing LDM-based inverse solvers typically require a large number of neural function evaluations (NFEs) and backpropagation through large pretrained components, leading to substantial computational costs and, in some cases, degraded reconstruction quality.