arXiv AI
Training-Free Hidden-State Refinement for Flow-Matching Image Generators
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WaiT for the Signal: Simple Frequency-Aware Flow-Matching
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Energy-Guided Flow Matching
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AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers
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CAT-Flow: Curvature-Adaptive sTeps for Flow Matching
The paper introduces CAT-Flow, a pair of lightweight, training‑free algorithms—CAT‑OV and CAT‑OT—that adapt step‑sizes during Flow Matching inference by estimating curvature in time or state space. These methods avoid extra neural evaluations and achieve constant‑order truncation error bounds. Experiments show that CAT‑OV and CAT‑OT improve image quality metrics across four text‑to‑image Flow Matching models, cutting the required generation steps by up to 40%.
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GenSyn10: A Multi-Generative AI Dataset For Benchmarking Image Classification
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