Matched-Learning-Rate Analysis of Attention Drift and Transfer Retention in Fine-Tuned CLIP

This paper investigates how adaptation methods (Full FT vs. LoRA) and optimization scale jointly shape attention drift and transfer retention in fine-tuned CLIP models. A controlled matched-learning-rate comparison reveals that the learning rate strongly modulates structural change, with Full FT showing marked contraction at higher rates while LoRA remains entropy-positive.