SAE-FT uses a sparse autoencoder on pre-trained CLIP visual representations to regularize fine-tuning by penalizing changes to semantically meaningful features, aiming for robust performance on ImageNet and distribution shifts.
StarFT: Robust fine-tuning of zero-shot models via spuriosity alignment.arXiv preprint arXiv:2505.13232, 2025
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Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models
SAE-FT uses a sparse autoencoder on pre-trained CLIP visual representations to regularize fine-tuning by penalizing changes to semantically meaningful features, aiming for robust performance on ImageNet and distribution shifts.