MG-CLIP preserves CLIP's modality gap by adaptively limiting fine-tuning epochs and compensates for its limits with a visual-space classifier, improving class-incremental learning without replay.
Benchmarking neu- ral network robustness to common corruptions and perturba- tions
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Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning
MG-CLIP preserves CLIP's modality gap by adaptively limiting fine-tuning epochs and compensates for its limits with a visual-space classifier, improving class-incremental learning without replay.