5 papers
LiLiCorr: Lightweight Likelihood Correlation of Parallel Drafts for Speculative Decoding
Matan Rusanovsky, Yoav Miron, Roy Uziel +4
Speculative decoding accelerates language-model inference by drafting future tokens that the target model verifies in parallel. A diffusion-style block head such as DFlash is an at…
Learn from Your Mistakes: Self-Correcting Masked Diffusion Models
Yair Schiff, Omer Belhasin, Roy Uziel +6
Masked diffusion models (MDMs) have emerged as a promising alternative to autoregressive models, enabling parallel token generation while achieving competitive performance. Despite…
CRoCoDiL: Continuous and Robust Conditioned Diffusion for Language
Roy Uziel, Omer Belhasin, Itay Levy +4
Masked Diffusion Models (MDMs) provide an efficient non-causal alternative to autoregressive generation but often struggle with token dependencies and semantic incoherence due to t…
Advancing Image Classification with Discrete Diffusion Classification Modeling
Omer Belhasin, Shelly Golan, Ran El-Yaniv +1
Image classification is a well-studied task in computer vision, and yet it remains challenging under high-uncertainty conditions, such as when input images are corrupted or trainin…
Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models
Omer Belhasin, Idan Kligvasser, George Leifman +7
Analyzing the cardiovascular system condition via Electrocardiography (ECG) is a common and highly effective approach, and it has been practiced and perfected over many decades. EC…