Scalable Patch-Level Self-Supervised Learning

arXiv:2610.10013 · cs.CV · Submitted 2026-10-07 · Read on arXiv

cs.CV

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Alignment — 31× in this paper · explained in 1 episode
• Regularization — 27× in this paper · explained in 3 episodes
• Self-Supervised Learning — 15× in this paper · explained in 8 episodes
• Clustering — 14× in this paper · explained in 2 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Redundancy — 10× in this paper · explained in 2 episodes
• Representation Learning — 10× in this paper · explained in 2 episodes
• Transformer — 10× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Instance Segmentation — 5× in this paper · explained in 3 episodes
• Cosine Similarity — 4× in this paper · explained in 3 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Linear Probing — 2× in this paper · explained in 2 episodes
• Linear probe — 2× in this paper · explained in 2 episodes
• Self-Distillation — 2× in this paper · explained in 7 episodes
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Predictive Coding — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning (SSL) — 1× in this paper · explained in 4 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
• Scaling Language-Free Visual Representation Learning
• Vision Pretraining for Dense Spatial Perception
• Self-Distillation of Hidden Layers for Self-Supervised Representation Learning
• V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning
• The information bottleneck method
• Representation Learning with Contrastive Predictive Coding
• Self-Supervised Learning by Estimating Twin Class Distributions

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