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cs.CV2025
Rethinking Test Time Scaling for Flow-Matching Generative Models
Qingtao Yu, Changlin Song, Minghao Sun +6
The performance of text-to-image diffusion models may be improved at test-time by scaling computation to search for a generated image that maximizes a given reward function. While…
cs.CV2025
NOVO: Unlearning-Compliant Vision Transformers
Soumya Roy, Soumya Banerjee, Vinay Verma +3
Machine unlearning (MUL) refers to the problem of making a pre-trained model selectively forget some training instances or class(es) while retaining performance on the remaining da…