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Found 5 papers, 3 papers with code
What do we learn from inverting CLIP models?
We employ an inversion-based approach to examine CLIP models.
Fast Adversarial Attacks on Language Models In One GPU Minute
Through human evaluations, we find that our untargeted attack causes Vicuna-7B-v1. 5 to produce ~15% more incorrect outputs when compared to LM outputs in the absence of our attack.
Identifying and Mitigating Model Failures through Few-shot CLIP-aided Diffusion Generation
One common reason for these failures is the occurrence of objects in backgrounds that are rarely seen during training.
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
Moreover, we show that watermarking methods are vulnerable to spoofing attacks where the attacker aims to have real images identified as watermarked ones, damaging the reputation of the developers.
Run-Off Election: Improved Provable Defense against Data Poisoning Attacks
Based on this approach, we propose DPA+ROE and FA+ROE defense methods based on Deep Partition Aggregation (DPA) and Finite Aggregation (FA) approaches from prior work.
