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MNIST
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IC-028
SPADE, an abstaining classifier built on top of ResNet, ViT, and VGG models, detects out-of-distribution and adversarial samples with provable guarantees.
[eval]
IC-1123
All seven published concept erasure methods applied to Stable Diffusion 1.4 can be circumvented by learned word embeddings, demonstrating that targeted concepts are input-filtered rather than truly removed from the model
[eval]
IC-1544
The latent spaces of pretrained foundational models across vision and text are not related by a single class of geometric transformations; the optimal alignment depends on the specific model pair, architecture, and dataset.
[eval]
IC-279
GP-LVM produces less structured latent representations and lower generative-classification accuracy than QEP-LVM on oil flow and MNIST
[eval]