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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

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Showing 151–200 of 971 papers

TitleStatusHype
aSAGA: Automatic Sleep Analysis with Gray Areas—0
Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness—0
A Meta Survey of Quality Evaluation Criteria in Explanation Methods—0
Argumentation Theoretical Frameworks for Explainable Artificial Intelligence—0
Additive-feature-attribution methods: a review on explainable artificial intelligence for fluid dynamics and heat transfer—0
Deep Learning Reproducibility and Explainable AI (XAI)—0
Argumentation-based Agents that Explain their Decisions—0
A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making—0
Deep Learning for predicting rate-induced tipping—0
A Means-End Account of Explainable Artificial Intelligence—0
A Data-Driven Framework for Identifying Investment Opportunities in Private Equity—0
A deep learning-enabled smart garment for accurate and versatile sleep conditions monitoring in daily life—0
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain—0
Deep Unsupervised Identification of Selected SNPs between Adapted Populations on Pool-seq Data—0
Data Representing Ground-Truth Explanations to Evaluate XAI Methods—0
Are Large Language Models the New Interface for Data Pipelines?—0
Alterfactual Explanations -- The Relevance of Irrelevance for Explaining AI Systems—0
Dataset | Mindset = Explainable AI | Interpretable AI—0
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models—0
Challenges for cognitive decoding using deep learning methods—0
A Psychological Theory of Explainability—0
ChatGPT or Human? Detect and Explain. Explaining Decisions of Machine Learning Model for Detecting Short ChatGPT-generated Text—0
Are Linear Regression Models White Box and Interpretable?—0
Clash of the Explainers: Argumentation for Context-Appropriate Explanations—0
A Review of Explainable Artificial Intelligence in Manufacturing—0
Classification and Explanation of Distributed Denial-of-Service (DDoS) Attack Detection using Machine Learning and Shapley Additive Explanation (SHAP) Methods—0
Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework—0
Classifying Simulated Gait Impairments using Privacy-preserving Explainable Artificial Intelligence and Mobile Phone Videos—0
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?—0
CNN-based explanation ensembling for dataset, representation and explanations evaluation—0
Challenges and Opportunities in Text Generation Explainability—0
Deciphering knee osteoarthritis diagnostic features with explainable artificial intelligence: A systematic review—0
A Lightweight IDS for Early APT Detection Using a Novel Feature Selection Method—0
A Data-Driven Exploration of Elevation Cues in HRTFs: An Explainable AI Perspective Across Multiple Datasets—0
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME—0
ARTxAI: Explainable Artificial Intelligence Curates Deep Representation Learning for Artistic Images using Fuzzy Techniques—0
Comparative Analysis of Hyperspectral Image Reconstruction Using Deep Learning for Agricultural and Biological Applications—0
Comparing interpretation methods in mental state decoding analyses with deep learning models—0
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey—0
Computational identification of ketone metabolism as a key regulator of sleep stability and circadian dynamics via real-time metabolic profiling—0
DCNFIS: Deep Convolutional Neuro-Fuzzy Inference System—0
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis—0
Concept-based Explainable Artificial Intelligence: A Survey—0
Concept-Based Explainable Artificial Intelligence: Metrics and Benchmarks—0
Concept Embedding Analysis: A Review—0
Enabling Verification of Deep Neural Networks in Perception Tasks Using Fuzzy Logic and Concept Embeddings—0
Concept Induction using LLMs: a user experiment for assessment—0
Asset Pricing and Deep Learning—0
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications—0
Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning—0
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