activity
20212026
most citedPrune Once for All: Sparse Pre-Trained Language Models

27 citations · 31 across the 9 of their papers we have counts for

collaborators

10 papers

cs.LG2026

VANDAM: Viewing a nucleotide sequence with DNA molecular priors

Jeremy Levy, Ariel Larey, Yury Nahshan +18

Contemporary Genomic Foundation Models (GFMs) rely on a DNA-as-a-string paradigm that employs masked token prediction objectives for pretraining. However, this abstraction does not…

cs.AI2026

JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures

Ariel Larey, Elay Dahan, Amit Bleiweiss +15

Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the "Laws of Nature". While effective at capturing local s…

cs.CV2024

A Multi-Modal Approach for Face Anti-Spoofing in Non-Calibrated Systems using Disparity Maps

Ariel Larey, Eyal Rond, Omer Achrack

Face recognition technologies are increasingly used in various applications, yet they are vulnerable to face spoofing attacks. These spoofing attacks often involve unique 3D struct…

cs.GR2023★ 1 cited

Facial Expression Re-targeting from a Single Character

Ariel Larey, Omri Asraf, Adam Kelder +3

Video retargeting for digital face animation is used in virtual reality, social media, gaming, movies, and video conference, aiming to animate avatars' facial expressions based on…

cs.LG2023

Harnessing Digital Pathology And Causal Learning To Improve Eosinophilic Esophagitis Dietary Treatment Assignment

Eliel Aknin, Ariel Larey, Julie M. Caldwell +14

Eosinophilic esophagitis (EoE) is a chronic, food antigen-driven, allergic inflammatory condition of the esophagus associated with elevated esophageal eosinophils. EoE is a top cau…

eess.IV2023★ 1 cited

Between Generating Noise and Generating Images: Noise in the Correct Frequency Improves the Quality of Synthetic Histopathology Images for Digital Pathology

Nati Daniel, Eliel Aknin, Ariel Larey +4

Artificial intelligence and machine learning techniques have the promise to revolutionize the field of digital pathology. However, these models demand considerable amounts of data,…

eess.IV2023

DEPAS: De-novo Pathology Semantic Masks using a Generative Model

Ariel Larey, Nati Daniel, Eliel Aknin +2

The integration of artificial intelligence into digital pathology has the potential to automate and improve various tasks, such as image analysis and diagnostic decision-making. Ye…

cs.AI2022★ 1 cited

Harnessing Artificial Intelligence to Infer Novel Spatial Biomarkers for the Diagnosis of Eosinophilic Esophagitis

Ariel Larey, Eliel Aknin, Nati Daniel +9

Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory condition of the esophagus associated with elevated esophageal eosinophils. Second only to gastroesophageal reflux…

cs.CL2021★ 27 cited

Prune Once for All: Sparse Pre-Trained Language Models

Ofir Zafrir, Ariel Larey, Guy Boudoukh +2

Transformer-based language models are applied to a wide range of applications in natural language processing. However, they are inefficient and difficult to deploy. In recent years…

cs.CV2021★ 1 cited

PECNet: A Deep Multi-Label Segmentation Network for Eosinophilic Esophagitis Biopsy Diagnostics

Nati Daniel, Ariel Larey, Eliel Aknin +9

Background. Eosinophilic esophagitis (EoE) is an allergic inflammatory condition of the esophagus associated with elevated numbers of eosinophils. Disease diagnosis and monitoring…