Explainable AI has 1,952 eligible papers in the latest 30-day evidence window, up 14% from the prior window, with representative work spanning Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data; A New Technique for AI Explainability using Feature Association Map; and Woodelf++: A Fast and Unified Partial Dependence Plot Algorithm for Decision Tree Ensembles.
Explainable AI shows 1,952 eligible recent papers and 1,952 commentary-ready papers in the current 30-day window, compared with 1,719 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers. 6 representative papers are preprints, so those findings should be treated as preliminary.
Explainable AI recorded 1,952 eligible papers in the latest 30-day window, compared with 1,719 in the prior 30-day window, making the current snapshot up 14% from the prior window.
1,952 recent vs 1,719 prior eligible papersExplainable Artificial Intelligence (XAI) contributes 1,952 eligible recent papers, including 1,952 papers with abstracts available for commentary.
1,952 papers in the leading clusterThe representative set includes Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data; A New Technique for AI Explainability using Feature Association Map; Woodelf++: A Fast and Unified Partial Dependence Plot Algorithm for Decision Tree Ensembles; A Quantitative Evaluation Framework for Explainable AI in Semantic Segmentation; and Explain Decisions, Not Just Predictions! An Evaluation Of Ai Agent Transparency. These papers anchor the page's claims and keep the brief tied to visible evidence.
8 representative papersExplainable Artificial Intelligence (XAI) accounts for 1,952 eligible recent papers, including 1,952 commentary-ready papers in this evidence window.
1,952 recent eligible papersThe selected papers cover Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data; A New Technique for AI Explainability using Feature Association Map; Woodelf++: A Fast and Unified Partial Dependence Plot Algorithm for Decision Tree Ensembles; and A Quantitative Evaluation Framework for Explainable AI in Semantic Segmentation. 6 representative papers are preprints, so those findings should be treated as preliminary.
8 representative papersA preprint from arXiv (Cornell University) in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A preprint from arXiv (Cornell University) in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A preprint from arXiv (Cornell University) in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A preprint from ISPRS annals of the photogrammetry, remote sensing and spatial information sciences in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A recent paper from Journal of the Association for Information Systems in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A preprint from arXiv (Cornell University) in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A preprint from arXiv (Cornell University) in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.
A recent paper from Information in the Explainable Artificial Intelligence (XAI) evidence packet, selected because it is recent, abstract-backed, and representative of this week's topic activity.