ViTAMINS: An Empirical Study of Training Self-Supervised Vision Transformers with Synthetic Hard Negatives

arXiv:2609.01041 · cs.CV, cs.AI, cs.LG · Submitted 2026-09-01 · Read on arXiv

cs.CV, cs.AI, cs.LG

Submitted: 2026-09-01

Updated: 2026-09-01

Code: https://github.com/giakoumoglou/vitamins

Terminology

• Transformer — 34× in this paper · explained in 2 episodes
• Contrastive Learning — 22× in this paper · explained in 5 episodes
• Accuracy — 17× in this paper · explained in 1 episode
• Distillation — 11× in this paper · explained in 2 episodes
• Self-Supervised Learning — 11× in this paper · explained in 8 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Self-Distillation — 9× in this paper · explained in 7 episodes
• Embeddings — 8× in this paper · explained in 2 episodes
• Representation Learning — 8× in this paper · explained in 2 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Transfer Learning — 6× in this paper · explained in 10 episodes
• Clustering — 5× in this paper · explained in 2 episodes
• Linear Probing — 5× in this paper · explained in 2 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Instance Segmentation — 3× in this paper · explained in 3 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Covariate Shift — 1× in this paper · explained in 2 episodes
• Distribution Matching — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Predictive Coding — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Revisiting Feature Prediction for Learning Visual Representations from Video

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