Cover Image

Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dembinsky, David, Lucieri, Adriano, Frolov, Stanislav, Najjar, Hiba, Watanabe, Ko, Dengel, Andreas
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Facilitated Fairness Assessment of AI-based Skin Lesion Classifiers Through GenAI-based Image Synthesis
by: Watanabe, Ko, et al.
Published: (2025)

The Directed Prediction Change - Efficient and Trustworthy Fidelity Assessment for Local Feature Attribution Methods
by: Iselborn, Kevin, et al.
Published: (2025)

Can Multitask Learning Enhance Model Explainability?
by: Najjar, Hiba, et al.
Published: (2025)

Intrinsic Explainability of Multimodal Learning for Crop Yield Prediction
by: Najjar, Hiba, et al.
Published: (2025)

Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features
by: Najjar, Hiba, et al.
Published: (2024)

Privacy Meets Explainability: A Comprehensive Impact Benchmark
by: Saifullah, Saifullah, et al.
Published: (2022)

Generating Counterfactual Trajectories with Latent Diffusion Models for Concept Discovery
by: Varshney, Payal, et al.
Published: (2024)

Opening the Black-Box: A Systematic Review on Explainable AI in Remote Sensing
by: Höhl, Adrian, et al.
Published: (2024)

Hyperspherical Forward-Forward with Prototypical Representations
by: Sarode, Shalini, et al.
Published: (2026)

SubZeroCore: A Submodular Approach with Zero Training for Coreset Selection
by: Moser, Brian B., et al.
Published: (2025)

Dynamic Attention-Guided Diffusion for Image Super-Resolution
by: Moser, Brian B., et al.
Published: (2023)

Unlocking Dataset Distillation with Diffusion Models
by: Moser, Brian B., et al.
Published: (2024)

Explainability of Sub-Field Level Crop Yield Prediction using Remote Sensing
by: Najjar, Hiba, et al.
Published: (2024)

Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-Resolution
by: Moser, Brian, et al.
Published: (2023)

HyperCore: Coreset Selection under Noise via Hypersphere Models
by: Moser, Brian B., et al.
Published: (2025)

Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning
by: Moser, Brian B., et al.
Published: (2024)

A Study in Dataset Distillation for Image Super-Resolution
by: Dietz, Tobias, et al.
Published: (2025)

Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution
by: Moser, Brian B., et al.
Published: (2024)

Diffusion Models, Image Super-Resolution And Everything: A Survey
by: Moser, Brian B., et al.
Published: (2024)

DWA: Differential Wavelet Amplifier for Image Super-Resolution
by: Moser, Brian B., et al.
Published: (2023)

Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning
by: Shanbhag, Arundhati S., et al.
Published: (2024)

A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
by: Donoso-Guzmán, Ivania, et al.
Published: (2025)

Federated Learning for Blind Image Super-Resolution
by: Moser, Brian B., et al.
Published: (2024)

A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift
by: Nagaraju, Sanath Budakegowdanadoddi, et al.
Published: (2024)

F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
by: Zheng, Xu, et al.
Published: (2024)

XAI-Guided Enhancement of Vegetation Indices for Crop Mapping
by: Najjar, Hiba, et al.
Published: (2024)

PupilSense: A Novel Application for Webcam-Based Pupil Diameter Estimation
by: Shah, Vijul, et al.
Published: (2024)

FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data
by: Anwar, Ahmed, et al.
Published: (2024)

From Private to Public: Benchmarking GANs in the Context of Private Time Series Classification
by: Mercier, Dominique, et al.
Published: (2023)

Exploring Physics-Informed Neural Networks for Crop Yield Loss Forecasting
by: Miranda, Miro, et al.
Published: (2024)

Explainable Human Activity Recognition: A Unified Review of Concepts and Mechanisms
by: Kundu, Mainak, et al.
Published: (2026)

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability
by: Zhang, Shichang, et al.
Published: (2025)

ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability
by: Zhu, Zhiyu, et al.
Published: (2025)

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

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

Evaluating Explainability in Machine Learning Predictions through Explainer-Agnostic Metrics
by: Munoz, Cristian, et al.
Published: (2023)

Procrustean Bed for AI-Driven Retrosynthesis: A Unified Framework for Reproducible Evaluation
by: Morgunov, Anton, et al.
Published: (2025)

VAEneu: A New Avenue for VAE Application on Probabilistic Forecasting
by: Koochali, Alireza, et al.
Published: (2024)

ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation
by: Nauen, Tobias Christian, et al.
Published: (2025)

PRISM: Diversifying Dataset Distillation by Decoupling Architectural Priors
by: Moser, Brian B., et al.
Published: (2025)