A Light Bilevel Refinement Aligns Self-Supervised Representations for Stronger Task-Specific Learning

arXiv:2609.33424 · cs.LG, cs.AI, cs.CV · Submitted 2026-09-27 · Read on arXiv

cs.LG, cs.AI, cs.CV

Submitted: 2026-09-27

Updated: 2026-09-27

Code: https://github.com/42X4X01XZ/ICLR27_20859

Terminology

• Fine-Tuning — 44× in this paper · explained in 5 episodes
• Adaptation — 21× in this paper · explained in 1 episode
• Accuracy — 20× in this paper · explained in 1 episode
• Transformer — 13× in this paper · explained in 2 episodes
• Alignment — 10× in this paper · explained in 1 episode
• Regularization — 10× in this paper · explained in 3 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Downstream Tasks — 8× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning — 6× in this paper · explained in 2 episodes
• Self-Supervised Learning — 6× in this paper · explained in 8 episodes
• Conference on Computer Vision and Pattern Recognition — 4× in this paper
• Fisher Information — 4× in this paper · explained in 3 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Alternation — 3× in this paper · explained in 1 episode
• Computational overhead — 3× in this paper · explained in 2 episodes
• Contrastive Learning — 3× in this paper · explained in 5 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Linear Probing — 3× in this paper · explained in 2 episodes
• Representational Similarity Analysis — 3× in this paper
• Transfer Learning — 3× in this paper · explained in 10 episodes
• AdamW Optimizer — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Low-Rank Adaptation (LoRA) — 2× in this paper · explained in 9 episodes
• Parameter-Efficient Fine-Tuning (PEFT) — 2× in this paper · explained in 4 episodes
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Computational Tractability — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Describable Textures Dataset — 1× in this paper
• Domain Shift — 1× in this paper · explained in 4 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Masked Autoencoder (MAE) — 1× in this paper · explained in 5 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning (SSL) — 1× in this paper · explained in 4 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes

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