Unverified50% confidenceFactExact time
Consistency models define a consistency function that requires the model to map any point on the same denoising trajectory to the same initial state, thereby enabling single-step or few-step sampling
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10/8/2026
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Unverified一致性正则化的基本假设是对同一输入样本施加不同扰动时模型输出应保持一致77% similarUnverifiedConsistency models achieve direct prediction of the endpoint of the denoising trajectory by training the network, theoretically enabling single-step generation.75% similarUnverifiedConsistency models attempt to compress the multi-step denoising process of diffusion models into 1–4 steps, theoretically capable of improving inference speed by 10–50 times.71% similarUnverifiedThe conjugate moment measure proposes using a single convex potential function W to simultaneously characterize the sampling distribution and the transport map, offering a path for generative modeling that differs from mainstream diffusion models.71% similarUnverifiedThe technical principle behind four-step generation typically comes from accelerated sampling paradigms such as Consistency Models or Flow Matching, which use distillation training to enable the model to accurately predict the denoising direction at sparse time steps.70% similar
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