unlearnable example

Towards Provably Unlearnable Examples via Bayes Error Optimization AAAI 2026 A3: Few-shot Prompt Learning of Unlearnable Examples with Cross-Modal Adversarial Feature Alignment CVPR 2025 Asynchronous Event Error-Minimizing Noise for Safeguarding Event Dataset ICCV 2025 Detecting and Corrupting Convolution-based Unlearnable Examples AAAI 2025 How Far Are We from True Unlearnability? ICLR 2025 MTL-UE: Learning to Learn Nothing for Multi-Task Learning ICML 2025 MYOPIA: Protecting Face Privacy from Malicious Personalized Text-to-Image Synthesis via Unlearnable Examples AAAI 2025 Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object Tracking ICCV 2025 Towards Operationalizing Right to Data Protection NAACL 2025 Detection and Defense of Unlearnable Examples AAAI 2024 Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously NeurIPS 2024 Game-Theoretic Unlearnable Example Generator AAAI 2024 MetaCloak: Preventing Unauthorized Subject-driven Text-to-image Diffusion-based Synthesis via Meta-learning CVPR 2024 One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment ICML 2024 Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise AAAI 2024 Ungeneralizable Examples CVPR 2024 Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need NeurIPS 2024 UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation NeurIPS 2024 One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks ICLR 2023 Transferable Unlearnable Examples ICLR 2023 Unlearnable Clusters: Towards Label-Agnostic Unlearnable Examples CVPR 2023 UPTON: Preventing Authorship Leakage from Public Text Release via Data Poisoning EMNLP 2023 Autoregressive Perturbations for Data Poisoning NeurIPS 2022 ConfounderGAN: Protecting Image Data Privacy with Causal Confounder NeurIPS 2022 Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning ICLR 2022