Cover Image

Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Goldwasser, Jeremy, Hooker, Giles
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Statistical Significance of Feature Importance Rankings
by: Goldwasser, Jeremy, et al.
Published: (2024)

Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space
by: Zhang, Yukai, et al.
Published: (2024)

Stabilizing Estimates of Shapley Values with Control Variates
by: Goldwasser, Jeremy, et al.
Published: (2023)

Evaluating Feature Attribution Methods in the Image Domain
by: Gevaert, Arne, et al.
Published: (2022)

Do Counterfactual Examples Complicate Adversarial Training?
by: Yeats, Eric, et al.
Published: (2024)

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

Adversarial Machine Learning: Attacking and Safeguarding Image Datasets
by: Chowdhury, Koushik
Published: (2025)

Latent Danger Zone: Distilling Unified Attention for Cross-Architecture Black-box Attacks
by: Li, Yang, et al.
Published: (2025)

Counterfactual Image Editing
by: Pan, Yushu, et al.
Published: (2024)

AIM: Additional Image Guided Generation of Transferable Adversarial Attacks
by: Li, Teng, et al.
Published: (2025)

LatentUM: Unleashing the Potential of Interleaved Cross-Modal Reasoning via a Latent-Space Unified Model
by: Jin, Jiachun, et al.
Published: (2026)

VIBE: Can a VLM Read the Room?
by: Chakraborty, Tania, et al.
Published: (2025)

Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability
by: Chen, Junxi, et al.
Published: (2024)

Diffusion Counterfactuals for Image Regressors
by: Ha, Trung Duc, et al.
Published: (2025)

Benchmarking Counterfactual Image Generation
by: Melistas, Thomas, et al.
Published: (2024)

LD-ViCE: Latent Diffusion Model for Video Counterfactual Explanations
by: Varshney, Payal, et al.
Published: (2025)

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

Latent Geometric Chords for Query-Efficient Decision-Based Adversarial Attacks
by: Khine, Ei Hmue, et al.
Published: (2026)

Benchmarking Transferable Adversarial Attacks
by: Jin, Zhibo, et al.
Published: (2024)

Transform-Dependent Adversarial Attacks
by: Tan, Yaoteng, et al.
Published: (2024)

Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
by: Varshney, Payal, et al.
Published: (2025)

Improving Adversarial Robustness of Attribution via Implicit Regularization
by: Mehrpanah, Amir, et al.
Published: (2026)

Training Feature Attribution for Vision Models
by: Bacha, Aziz, et al.
Published: (2025)

Latent Forcing: Reordering the Diffusion Trajectory for Pixel-Space Image Generation
by: Baade, Alan, et al.
Published: (2026)

Enabling Heterogeneous Adversarial Transferability via Feature Permutation Attacks
by: Wu, Tao, et al.
Published: (2025)

Latent Diffusion Inversion Requires Understanding the Latent Space
by: Rao, Mingxing, et al.
Published: (2025)

Adversarial Examples Are Not Real Features
by: Li, Ang, et al.
Published: (2023)

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

Dynamic Label Adversarial Training for Deep Learning Robustness Against Adversarial Attacks
by: Liu, Zhenyu, et al.
Published: (2024)

Scaling Laws for Black box Adversarial Attacks
by: Liu, Chuan, et al.
Published: (2024)

Learning Counterfactually Decoupled Attention for Open-World Model Attribution
by: Zheng, Yu, et al.
Published: (2025)

Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations
by: Mitcheff, Mahsa, et al.
Published: (2025)

MedIL: Implicit Latent Spaces for Generating Heterogeneous Medical Images at Arbitrary Resolutions
by: Spears, Tyler, et al.
Published: (2025)

Image Counterfactual Sensitivity Analysis for Detecting Unintended Bias
by: Denton, Remi, et al.
Published: (2019)

Image Clustering Algorithm Based on Self-Supervised Pretrained Models and Latent Feature Distribution Optimization
by: Zhu, Qiuyu, et al.
Published: (2024)

What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization
by: Thomas, Xavier, et al.
Published: (2025)

Aligning Latent Spaces with Flow Priors
by: Li, Yizhuo, et al.
Published: (2025)

Similarity of Neural Architectures using Adversarial Attack Transferability
by: Hwang, Jaehui, et al.
Published: (2022)

Unified Latents (UL): How to train your latents
by: Heek, Jonathan, et al.
Published: (2026)

Pixel-level Counterfactual Contrastive Learning for Medical Image Segmentation
by: Lafargue-Hauret, Marceau, et al.
Published: (2026)