AI RESEARCH
Probability-Conserving Flow Guidance
arXiv CS.AI
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ArXi:2605.20079v1 Announce Type: cross Diffusion and flow-based generative models dominate visual synthesis, with guidance aligning samples to user input and improving perceptual quality. However, Classifier-Free Guidance (CFG) and extrapolation-based methods are heuristic linear combinations of velocities/scores that ignore the generative manifold geometry, breaking probability conservation and driving samples off the learned manifold under strong guidance.