collaborators

15 papers

cs.CV2026

Self-supervised DXA representations encode multi-system disease risk, biological aging and heritability

Gil Sasson, Zachary Levine, Smadar Shilo +9

Whole-body dual-energy X-ray absorptiometry (DXA) scans are routinely acquired to measure bone density and regional body composition, leaving their spatial structure largely unused…

cs.CV2026

VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation

Hongyang Du, Junjie Ye, Xiaoyan Cong +7

While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deforma…

cs.LG2026

Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations

Yilun Kuang, Yash Dagade, Tim G. J. Rudner +2

Joint-Embedding Predictive Architectures (JEPA) learn view-invariant representations and admit projection-based distribution matching for collapse prevention. Existing approaches r…

cs.CV2026

A Lightweight Library for Energy-Based Joint-Embedding Predictive Architectures

Basile Terver, Randall Balestriero, Megi Dervishi +8

We present EB-JEPA, an open-source library for learning representations and world models using Joint-Embedding Predictive Architectures (JEPAs). JEPAs learn to predict in represent…

cs.LG2026

Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA

Hai Huang, Yann LeCun, Randall Balestriero

Large Language Models (LLMs) obey consistent scaling laws -- empirical power-law fits that predict how loss decreases with compute, data, and parameters. While predictive, these la…

cs.AI2026

stable-worldmodel-v1: Reproducible World Modeling Research and Evaluation

Lucas Maes, Quentin Le Lidec, Dan Haramati +4

World Models have emerged as a powerful paradigm for learning compact, predictive representations of environment dynamics, enabling agents to reason, plan, and generalize beyond di…