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EigDiff: Eigensample Diffusion - or how to significantly reduce training dataset size with marginal performance variation?
Andrei Jarca, Vlad Hondru, Florinel-Alin Croitoru +1
Diffusion models are notoriously expensive to train, requiring large-scale datasets to learn how to gradually reverse the noise from images over multiple small denoising steps. Cur…
DF-MoE: Generalizable Deepfake Detection via Multimodal Sparse Mixture-of-Experts
Vlad Hondru, Florinel Alin Croitoru, Iuliana Georgescu +2
Audio-visual deepfake detection is an actively studied topic, where one of the main challenges is to develop detectors able to generalize across deepfake generation methods. We con…
MTL-MAD: Multi-Task Learners are Effective Medical Anomaly Detectors
Bogdan Alexandru Bercean, Florinel Alin Croitoru, Vlad Hondru +3
Anomaly detection in medical images is a challenging task, since anomalies are not typically available during training. Recent methods leverage a single pretext task coupled with a…
Curriculum-DPO++: Direct Preference Optimization via Data and Model Curricula for Text-to-Image Generation
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu +2
Direct Preference Optimization (DPO) has been proposed as an effective and efficient alternative to reinforcement learning from human feedback (RLHF). However, neither RLHF nor DPO…