SOTAVerified

Explainable artificial intelligence

XAI refers to methods and techniques in the application of artificial intelligence (AI) such that the results of the solution can be understood by humans. It contrasts with the concept of the "black box" in machine learning where even its designers cannot explain why an AI arrived at a specific decision. XAI may be an implementation of the social right to explanation. XAI is relevant even if there is no legal right or regulatory requirement—for example, XAI can improve the user experience of a product or service by helping end users trust that the AI is making good decisions. This way the aim of XAI is to explain what has been done, what is done right now, what will be done next and unveil the information the actions are based on. These characteristics make it possible (i) to confirm existing knowledge (ii) to challenge existing knowledge and (iii) to generate new assumptions.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 971 papers

TitleStatusHype
Assessing the Efficacy of Deep Learning Approaches for Facial Expression Recognition in Individuals with Intellectual Disabilities—0
Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability—0
Enhancing UAV Security Through Zero Trust Architecture: An Advanced Deep Learning and Explainable AI Analysis—0
Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution—0
Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders—0
Evolutionary approaches to explainable machine learning—0
Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space—0
EVolutionary Independent DEtermiNistiC Explanation—0
Evolved Explainable Classifications for Lymph Node Metastases—0
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks—0
EXACT: Towards a platform for empirically benchmarking Machine Learning model explanation methods—0
Examining the Rat in the Tunnel: Interpretable Multi-Label Classification of Tor-based Malware—0
Example-Based Explainable AI and its Application for Remote Sensing Image Classification—0
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches—0
Explainability for identification of vulnerable groups in machine learning models—0
Explainability in Deep Reinforcement Learning—0
Explainability in Deep Reinforcement Learning, a Review into Current Methods and Applications—0
Carefully choose the baseline: Lessons learned from applying XAI attribution methods for regression tasks in geoscience—0
Applying XAI based unsupervised knowledge discovering for Operation modes in a WWTP. A real case: AQUAVALL WWTP—0
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence—0
Explainability is NOT a Game—0
Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals—0
CAT: Concept-level backdoor ATtacks for Concept Bottleneck Models—0
Explainability of deep vision-based autonomous driving systems: Review and challenges—0
Explainability through uncertainty: Trustworthy decision-making with neural networks—0
Explainability via Responsibility—0
Explainable Activity Recognition for Smart Home Systems—0
Explainable AI-Based Interface System for Weather Forecasting Model—0
Explainable AI-based Intrusion Detection System for Industry 5.0: An Overview of the Literature, associated Challenges, the existing Solutions, and Potential Research Directions—0
A Novel Approach for Semiconductor Etching Process with Inductive Biases—0
Explainable AI: current status and future directions—0
Explainable AI does not provide the explanations end-users are asking for—0
Explainable AI-Driven Neural Activity Analysis in Parkinsonian Rats under Electrical Stimulation—0
Most General Explanations of Tree Ensembles (Extended Version)—0
Challenges and Opportunities in Text Generation Explainability—0
Explainable AI for Earth Observation: Current Methods, Open Challenges, and Opportunities—0
Explainable AI for Embedded Systems Design: A Case Study of Static Redundant NVM Memory Write Prediction—0
Explainable AI for tailored electricity consumption feedback -- an experimental evaluation of visualizations—0
Explainable Artificial Intelligence: a Systematic Review—0
Explainable AI for tool wear prediction in turning—0
Explainable AI-Guided Efficient Approximate DNN Generation for Multi-Pod Systolic Arrays—0
Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method—0
Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability—0
Explainable Artificial Intelligence and its potential within Industry—0
Explainable AI Integrated Feature Engineering for Wildfire Prediction—0
Explainable AI is Dead, Long Live Explainable AI! Hypothesis-driven decision support—0
Explainable AI meets Healthcare: A Study on Heart Disease Dataset—0
Explainable AI Methods for Multi-Omics Analysis: A Survey—0
Explainable AI needs formal notions of explanation correctness—0
Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising—0
Show:102550
← PrevPage 7 of 20Next →

No leaderboard results yet.