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cs.LG2026
Composing and Steering Diffusion Models with Generalized Feynman-Kac Correctors
Wael Mattar, Daniel Freedman
Diffusion models have become the leading paradigm in generative modeling, yet many applications require sampling from distributions that are not those of any single pretrained mode…
cs.LG2024★ 2 cited
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models
Regev Cohen, Idan Kligvasser, Ehud Rivlin +1
The pursuit of high perceptual quality in image restoration has driven the development of revolutionary generative models, capable of producing results often visually indistinguish…
cs.LG2024
Early Time Classification with Accumulated Accuracy Gap Control
Liran Ringel, Regev Cohen, Daniel Freedman +2
Early time classification algorithms aim to label a stream of features without processing the full input stream, while maintaining accuracy comparable to that achieved by applying…