arXiv AI By Achleshwar Luthra, Lucas Bryant, Tracy Zhu, Tomer Galanti

Which Tasks Survive Self-Supervised Learning?

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arXiv Computer Vision
1d ago

Scalable Patch-Level Self-Supervised Learning

arXiv:2610.10013v1 Announce Type: new Abstract: Self-supervised learning (SSL) at scale produces powerful visual representations. However, most scalable SSL methods rely on ad hoc combinations of mul...

By Maximilian Seitzer, Gabriele Trivigno, Anton\'in Vobeck\'y, Seungeun Yi, Maxime Oquab, Huy V. Vo, Oriane Sim\'eoni, Piotr Bojanowski
arXiv Machine Learning
Aug 20

Pretraining Reusable Inference Across Views with Synthetic Task Priors

The paper introduces SIMPLE, a prior‑fitted multi‑view in‑context learner that learns a reusable, task‑conditioned inference procedure instead of a fixed fusion function. By generating synthetic task priors in embedding space, SIMPLE can handle diverse view configurations, class structures, and missingness patterns. Experiments on multi‑view and multi‑omics benchmarks show that a frozen SIMPLE model performs competitively, and lightweight adapter calibration further improves performance across most datasets.

By Jielong Lu, Zhihao Wu, Jiajun Yu, Zhaoliang Chen, Haishuai Wang