Cover Image

The Anatomy of Adversarial Attacks: Concept-based XAI Dissection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mikriukov, Georgii, Schwalbe, Gesina, Motzkus, Franz, Bade, Korinna
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Local Concept Embeddings for Analysis of Concept Distributions in Vision DNN Feature Spaces
by: Mikriukov, Georgii, et al.
Published: (2023)

Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability
by: Mikriukov, Georgii, et al.
Published: (2023)

Locally Testing Model Detections for Semantic Global Concepts
by: Motzkus, Franz, et al.
Published: (2024)

On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
by: Schwalbe, Gesina, et al.
Published: (2025)

Weakly Supervised Concept Learning for Object-centric Visual Reasoning
by: Tiwari, Sparsh, et al.
Published: (2026)

Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go?
by: Lee, Jae Hee, et al.
Published: (2024)

Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study
by: Mitra, Pallavi, et al.
Published: (2024)

NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques
by: Hryniewska-Guzik, Weronika, et al.
Published: (2024)

Hard-label based Small Query Black-box Adversarial Attack
by: Park, Jeonghwan, et al.
Published: (2024)

Unveiling Ontological Commitment in Multi-Modal Foundation Models
by: Keser, Mert, et al.
Published: (2024)

FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks
by: Yang, Hunmin, et al.
Published: (2024)

Human-Centered Evaluation of XAI Methods
by: Dawoud, Karam, et al.
Published: (2023)

Impact of Adversarial Attacks on Deep Learning Model Explainability
by: Nur, Gazi Nazia, et al.
Published: (2024)

eXIAA: eXplainable Injections for Adversarial Attack
by: Pesce, Leonardo, et al.
Published: (2025)

Adversarial Attacks Leverage Interference Between Features in Superposition
by: Stevinson, Edward, et al.
Published: (2025)

Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute Recognition
by: Kong, Weizhe, et al.
Published: (2025)

SORA: Free Second-Order Attacks in Fast Adversarial Training
by: Teymourian, Mazdak, et al.
Published: (2026)

ADBA:Approximation Decision Boundary Approach for Black-Box Adversarial Attacks
by: Wang, Feiyang, et al.
Published: (2024)

X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
by: Huang, Hanxun, et al.
Published: (2025)

Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks
by: Blücher, Stefan, et al.
Published: (2024)

XAI for Skin Cancer Detection with Prototypes and Non-Expert Supervision
by: Correia, Miguel, et al.
Published: (2024)

Towards a Novel Measure of User Trust in XAI Systems
by: Miró-Nicolau, Miquel, et al.
Published: (2024)

Uncertainty Propagation in XAI: A Comparison of Analytical and Empirical Estimators
by: Chiaburu, Teodor, et al.
Published: (2025)

Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations
by: Kulkarni, Pranav, et al.
Published: (2024)

Theoretical Analysis of Relative Errors in Gradient Computations for Adversarial Attacks with CE Loss
by: Yu, Yunrui, et al.
Published: (2025)

Memory Efficient Full-gradient Attacks (MEFA) Framework for Adversarial Defense Evaluations
by: Du, Yuan, et al.
Published: (2026)

Evaluation Cards for XAI Metrics
by: Gipiškis, Rokas, et al.
Published: (2026)

BankTweak: Adversarial Attack against Multi-Object Trackers by Manipulating Feature Banks
by: Shin, Woojin, et al.
Published: (2024)

Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
by: Lao, Dong, et al.
Published: (2025)

Concept-based Adversarial Attack: a Probabilistic Perspective
by: Zhang, Andi, et al.
Published: (2025)

Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
by: Feng, Yunzhen, et al.
Published: (2024)

GRILL: Restoring Gradient Signal in Ill-Conditioned Layers for More Effective Adversarial Attacks on Autoencoders
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2025)

Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks
by: Yang, Hunmin, et al.
Published: (2024)

Explainable artificial intelligence (XAI): from inherent explainability to large language models
by: Mumuni, Fuseini, et al.
Published: (2025)

Break the Visual Perception: Adversarial Attacks Targeting Encoded Visual Tokens of Large Vision-Language Models
by: Wang, Yubo, et al.
Published: (2024)

Tailoring Adversarial Attacks on Deep Neural Networks for Targeted Class Manipulation Using DeepFool Algorithm
by: Labib, S. M. Fazle Rabby, et al.
Published: (2023)

Real-world Adversarial Defense against Patch Attacks based on Diffusion Model
by: Wei, Xingxing, et al.
Published: (2024)

Dissecting Representation Misalignment in Contrastive Learning via Influence Function
by: Hu, Lijie, et al.
Published: (2024)

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization
by: Lee, Dongyeun, et al.
Published: (2025)

Random Sampling for Diffusion-based Adversarial Purification
by: Zhang, Jiancheng, et al.
Published: (2024)