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cs.LG2026
Unlocking the Duality between Flow and Field Matching
Daniil Shlenskii, Alexander Varlamov, Nazar Buzun +1
Conditional Flow Matching (CFM) unifies conventional generative paradigms such as diffusion models and flow matching. Interaction Field Matching (IFM) is a newer framework that gen…
cs.LG2025
VARAN: Variational Inference for Self-Supervised Speech Models Fine-Tuning on Downstream Tasks
Daria Diatlova, Nikita Balagansky, Alexander Varlamov +1
Conventional methods for aggregating layers in fine-tuned self-supervised speech models, such as using the final layer or weighted sum, suffer from information bottlenecks and stat…
cs.LG2024
METR: Image Watermarking with Large Number of Unique Messages
Alexander Varlamov, Daria Diatlova, Egor Spirin
Improvements in diffusion models have boosted the quality of image generation, which has led researchers, companies, and creators to focus on improving watermarking algorithms. Thi…