Awaken, Then Scale: Tiny Adaptation for MRI Reconstruction

arXiv:2609.31813 · eess.IV, cs.CV · Submitted 2026-09-25 · Read on arXiv

eess.IV, cs.CV

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Calibration — 38× in this paper · explained in 7 episodes
• Adaptation — 37× in this paper · explained in 1 episode
• Pruning — 16× in this paper · explained in 4 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Dormant Awakening — 3× in this paper
• Generalization — 3× in this paper · explained in 13 episodes
• Transfer Learning — 3× in this paper · explained in 10 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Meta-learning — 2× in this paper · explained in 2 episodes
• Self-Supervised Learning — 2× in this paper · explained in 8 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• FAM: fast adaptive federated meta-learning
• SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning
• fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

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