Detecting Adversarial Images through Response Profiles of Vision-Language Models

arXiv:2610.10436 · cs.CV · Submitted 2026-10-07 · Read on arXiv

cs.CV

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Embeddings — 17× in this paper · explained in 2 episodes
• AUC — 14× in this paper · explained in 2 episodes
• Ablation — 12× in this paper · explained in 1 episode
• Adversarial Examples — 12× in this paper · explained in 2 episodes
• Vision-language models — 9× in this paper · explained in 2 episodes
• Adversarial Attacks — 4× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Adjacency Matrix — 3× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Semantic Alignment — 3× in this paper · explained in 3 episodes
• Adversarial Robustness — 2× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Distribution Shift — 2× in this paper · explained in 6 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Graph Construction — 2× in this paper · explained in 3 episodes
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Influence Functions — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Out-of-Distribution (OOD) Detection — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Drift — 1× in this paper · explained in 3 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Detecting Adversarial Samples from Artifacts
• On the (Statistical) Detection of Adversarial Examples
• An Empirical Analysis of VLM-based OOD Detection: Mechanisms, Advantages, and Sensitivity
• Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey

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