Nairouz Mrabah

In few-shot CLIP adaptation, support-set gradient magnitudes are badly miscalibrated, yet the signs of a small top-magnitude subset still point toward descent. SignSparseSGD and DynSignSparseSGD therefore use gradient magnitude only to choose where to update and fixed-magnitude signs to decide how, keeping no first- or second-moment state. Across 11 datasets, three CLIP backbones and five shot levels, the dynamic variant has the highest mean accuracy in all 15 backbone–shot settings, reaching 72.7% on ViT-B/16 at one shot, 1.3 points above SO.

In few-shot CLIP adaptation, support-set gradient magnitudes are badly miscalibrated, yet the signs of a small top-magnitude subset still point toward descent. SignSparseSGD and DynSignSparseSGD therefore use gradient magnitude only to choose where to update and fixed-magnitude signs to decide how, keeping no first- or second-moment state. Across 11 datasets, three CLIP backbones and five shot levels, the dynamic variant has the highest mean accuracy in all 15 backbone–shot settings, reaching 72.7% on ViT-B/16 at one shot, 1.3 points above SO.