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This paper proposes Deep Bio-Hashing Network (DBHN) for privacy-preserving finger vein recognition, achieving end-to-end cancelable recognition and proposes a Deep Bio-Hashing layer to tackle the security problem caused by stolen tokenized random numbers.
The Modality Masking Mechanism (M3), an embarrassingly simple, training-only strategy that requires no architectural changes or large-scale robot pretraining, is introduced to improve robustness of query-based VLA policies for bimanual manipulation.
Inspired by Bayesian posterior inference, this work reformulate backdoor detection as a representation-conditioned image likelihood estimation problem parameterized by a conditional diffusion generative model, and fine-tune a pretrained diffusion model, leveraging its generative prior to map data onto the natural image...
Deep learning models for point cloud classification are highly vulnerable to adversarial attacks, while recent advances in diffusion-based purification have shown promising defensive performance. However, existing diffusion-based purification methods harbor two fundamental limitations. First, a distributional gap arise...
A new attack-agnostic, model-agnostic, and modality-agnostic black-box test-time defense paradigm, inspired by the Platonic Representation Hypothesis, that can perform both representation detection and purification, and achieves substantial performance gains across multiple attacks.
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