Explainable artificial intelligence

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

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

Subtasks archive 2025-07-28

3 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 305 papers with code (971 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.

• Axiomatic Attribution for Deep Networks
  4 Mar 2017 40 repositories listed Syntology ran 36 of 56 samples · 20 unverified · 17 pointer-only (licence)
  We study the problem of attributing the prediction of a deep network to its input features, a problem previously studied by several other works.
• GNNExplainer: Generating Explanations for Graph Neural Networks
  10 Mar 2019 12 repositories listed Syntology ran 1 of 22 samples · 21 unverified
  We formulate GNNExplainer as an optimization task that maximizes the mutual information between a GNN's prediction and distribution of possible subgraph structures.
• 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.
• MEGAN: Multi-Explanation Graph Attention Network
  23 Nov 2022 3 repositories listed
  Unlike existing graph explainability methods, our network can produce node and edge attributional explanations along multiple channels, the number of which is independent of task specifications.
• 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…
• Entropy-based Logic Explanations of Neural Networks
  12 Jun 2021 3 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  Explainable artificial intelligence has rapidly emerged since lawmakers have started requiring interpretable models for safety-critical domains.
• 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.
• 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…
• 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.
• The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems
  30 Jun 2023 2 repositories listed
  To capture these changes, Explainable Artificial Intelligence tools are used to compare models trained on datasets before and after balancing.
• 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?
• TE2Rules: Explaining Tree Ensembles using Rules
  29 Jun 2022 2 repositories listed
  Tree Ensemble (TE) models, such as Gradient Boosted Trees, often achieve optimal performance on tabular datasets, yet their lack of transparency poses challenges for comprehending their decision logic.
• 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.
• 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.
• Counterfactual Shapley Additive Explanations
  27 Oct 2021 2 repositories listed Syntology ran 0 of 13 samples · 13 unverified
  Feature attributions are a common paradigm for model explanations due to their simplicity in assigning a single numeric score for each input feature to a model.
• Explaining deep learning models for spoofing and deepfake detection with SHapley Additive exPlanations
  7 Oct 2021 2 repositories listed
  Substantial progress in spoofing and deepfake detection has been made in recent years.
• Logic Explained Networks
  11 Aug 2021 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  The language used to communicate the explanations must be formal enough to be implementable in a machine and friendly enough to be understandable by a wide audience.
• 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.
• Towards Rigorous Interpretations: a Formalisation of Feature Attribution
  26 Apr 2021 2 repositories listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)
  Feature attribution is often loosely presented as the process of selecting a subset of relevant features as a rationale of a prediction.
• 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.
• Explaining How Deep Neural Networks Forget by Deep Visualization
  3 May 2020 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Explaining the behaviors of deep neural networks, usually considered as black boxes, is critical especially when they are now being adopted over diverse aspects of human life.
• 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.
• 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.
• SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines
  15 May 2018 2 repositories listed Syntology ran 4 of 5 samples · 1 unverified
  Recurrent and convolutional neural networks comprise two distinct families of models that have proven to be useful for encoding natural language utterances.
• Communicating Smartly in the Molecular Domain: Neural Networks in the Internet of Bio-Nano Things
  25 Jun 2025 1 repository listed
  Recent developments in the Internet of Bio-Nano Things (IoBNT) are laying the groundwork for innovative applications across the healthcare sector.
• midr: Learning from Black-Box Models by Maximum Interpretation Decomposition
  10 Jun 2025 1 repository listed
  The use of appropriate methods of Interpretable Machine Learning (IML) and eXplainable Artificial Intelligence (XAI) is essential for adopting black-box predictive models in fields where model and prediction…
• Do Protein Transformers Have Biological Intelligence?
  7 Jun 2025 1 repository listed
  To achieve our goal, we first introduce a protein function dataset, namely Protein-FN, providing over 9000 protein data with meaningful labels.
• TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
  5 Jun 2025 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Recent explainable artificial intelligence (XAI) methods for time series primarily estimate point-wise attribution magnitudes, while overlooking the directional impact on predictions, leading to suboptimal…

Syntology lines on 13 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.