Explainable Artificial Intelligence (XAI)

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 296 papers with code (1,041 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• RISE: Randomized Input Sampling for Explanation of Black-box Models
  19 Jun 2018 13 repositories listed Syntology ran 1 of 34 samples · 33 unverified · 10 pointer-only (licence)
  We compare our approach to state-of-the-art importance extraction methods using both an automatic deletion/insertion metric and a pointing metric based on human-annotated object segments.
• Proposed Guidelines for the Responsible Use of Explainable Machine Learning
  8 Jun 2019 5 repositories listed
  Explainable machine learning (ML) enables human learning from ML, human appeal of automated model decisions, regulatory compliance, and security audits of ML models.
• Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy
  24 Jun 2021 4 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Deep Neural Networks (DNNs) are known to be strong predictors, but their prediction strategies can rarely be understood.
• Explanations Based on Item Response Theory (eXirt): A Model-Specific Method to Explain Tree-Ensemble Model in Trust Perspective
  18 Oct 2022 3 repositories listed
  In recent years, XAI researchers have been formalizing proposals and developing new methods to explain black box models, with no general consensus in the community on which method to use to explain these models, with…
• AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark
  9 Jul 2018 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Explainable Artificial Intelligence (XAI) is targeted at understanding how models perform feature selection and derive their classification decisions.
• Time series saliency maps: explaining models across multiple domains
  19 May 2025 2 repositories listed
  These results demonstrate the ability of cross-domain integrated gradients to provide semantically meaningful insights in time-series models that are impossible with traditional time-domain saliency.
• Interpreting Object-level Foundation Models via Visual Precision Search
  25 Nov 2024 2 repositories listed
  Advances in multimodal pre-training have propelled object-level foundation models, such as Grounding DINO and Florence-2, in tasks like visual grounding and object detection.
• An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records
  13 Jun 2024 2 repositories listed
  Electronic healthcare records are vital for patient safety as they document conditions, plans, and procedures in both free text and medical codes.
• Local Concept Embeddings for Analysis of Concept Distributions in Vision DNN Feature Spaces
  24 Nov 2023 2 repositories listed
  Therefore, state-of-the-art supervised Concept-based eXplainable Artificial Intelligence (C-XAI) methods associate user-defined concepts like ``car'' each with a single vector in the DNN latent space (concept embedding…
• IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
  17 Oct 2023 2 repositories listed
  Previous research on behavior-based attack detection for networks of IoT devices has resulted in machine learning models whose ability to adapt to unseen data is limited and often not demonstrated.
• PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans
  25 Aug 2023 2 repositories listed
  Nearest neighbors (NN) are traditionally used to compute final decisions, e.
• FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods
  11 Aug 2023 2 repositories listed Syntology ran 5 of 13 samples · 8 unverified
  Using our tools, we report results for 24 different combinations of neural models and XAI methods, demonstrating the strengths and weaknesses of the assessed methods in a fully automatic and systematic manner.
• Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees
  27 Jan 2023 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  For the trustworthy application of XAI, in particular for high-stake decisions, a more global model understanding is required.
• Black Box Model Explanations and the Human Interpretability Expectations -- An Analysis in the Context of Homicide Prediction
  19 Oct 2022 2 repositories listed
  ", "Can explanations generated by XAI methods meet human expectation of Interpretations?
• ferret: a Framework for Benchmarking Explainers on Transformers
  2 Aug 2022 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  With ferret, users can visualize and compare transformers-based models output explanations using state-of-the-art XAI methods on any free-text or existing XAI corpora.
• "Even if ..." -- Diverse Semifactual Explanations of Reject
  5 Jul 2022 2 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  In this work, we propose to explain rejects by semifactual explanations, an instance of example-based explanation methods, which them self have not been widely considered in the XAI community yet.
• OpenXAI: Towards a Transparent Evaluation of Model Explanations
  22 Jun 2022 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  OpenXAI comprises of the following key components: (i) a flexible synthetic data generator and a collection of diverse real-world datasets, pre-trained models, and state-of-the-art feature attribution methods, and (ii)…
• From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation
  7 Jun 2022 2 repositories listed
  In this work we introduce the Concept Relevance Propagation (CRP) approach, which combines the local and global perspectives and thus allows answering both the "where" and "what" questions for individual predictions.
• OmniXAI: A Library for Explainable AI
  1 Jun 2022 2 repositories listed
  We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpretable machine learning techniques to…
• GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
  19 Apr 2022 2 repositories listed
  The number of information systems (IS) studies dealing with explainable artificial intelligence (XAI) is currently exploding as the field demands more transparency about the internal decision logic of machine learning…
• Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AI
  30 Dec 2021 2 repositories listed
  This paper quantifies the quality of heatmap-based eXplainable AI (XAI) methods w.
• Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction
  1 Jul 2021 2 repositories listed
  Advances in machine learning have led to graph neural network-based methods for drug discovery, yielding promising results in molecular design, chemical synthesis planning, and molecular property prediction.
• Revealing drivers and risks for power grid frequency stability with explainable AI
  7 Jun 2021 2 repositories listed
  Stable operation of the electrical power system requires the power grid frequency to stay within strict operational limits.
• LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information
  13 Apr 2021 2 repositories listed
  Artificial Intelligence (AI) has a tremendous impact on the unexpected growth of technology in almost every aspect.
• BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations
  5 Dec 2020 2 repositories listed
  Given the pressing need for assuring algorithmic transparency, Explainable AI (XAI) has emerged as one of the key areas of AI research.
• Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic Dataset
  7 Sep 2020 2 repositories listed
  Heatmaps can be appealing due to the intuitive and visual ways to understand them but assessing their qualities might not be straightforward.
• Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI
  16 Mar 2020 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  The rise of deep learning in today's applications entailed an increasing need in explaining the model's decisions beyond prediction performances in order to foster trust and accountability.
• On the Explanation of Machine Learning Predictions in Clinical Gait Analysis
  16 Dec 2019 2 repositories listed
  Machine learning (ML) is increasingly used to support decision-making in the healthcare sector.
• TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP
  2 Dec 2019 2 repositories listed
  While state-of-the-art NLP explainability (XAI) methods focus on explaining per-sample decisions in supervised end or probing tasks, this is insufficient to explain and quantify model knowledge transfer during…
• Do Not Trust Additive Explanations
  27 Mar 2019 2 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  Explainable Artificial Intelligence (XAI)has received a great deal of attention recently.

Syntology lines on 10 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.