# Authors Title Details Date Pdf/Links/Bibtex Keywords
25Ephrem Tibebe Mekonnen; Longo L., Dondio P.LOMATCE: LOcal Model-Agnostic Time-series Classification Explanations IEEE Access 2025 Time series analysis • Adaptation models • Explainable AI • Predictive models • Data models • Closed box • Perturbation methods • Computational modeling • Deep learning • Kernel • Explainable Artificial Intelligence • Model-agnostic • Time series • Post hoc • Deep learning • XAI
10.1109/ACCESS.2025.3625442
24Vilone G., Longo L. Evaluating Argumentation Graphs as Global Explainable Surrogate Models for Dense Neural Networks and Their Comparison with Decision Trees eXplainable Artificial Intelligence, The World Conference (xAI-2025) 2025 Logical Analysis • Graph Theory • Graph Theory in Probability • Machine Learning • Reasoning • Symbolic AI • Explainable AI • Surrogate models • Computational Argumentation • Rule-based systems • Decision-trees • Dense Neural Networks • Deep learning
10.1007/978-3-032-08333-3_5
23Ahmed T., Biecek P. Longo L. Latent Space Interpretation and Mechanistic Clipping of Subject-Specific Variational Autoencoders of EEG Topographic Maps for Artefacts Reduction eXplainable Artificial Intelligence, The World Conference (xAI-2025) 2025 Electroencephalography • Spectral topographic maps • Subject-specific • Variational autoencoder • Latent space • interpretability • Artefacts removal • Deep learning • full automation • explainable AI
10.1007/978-3-032-08327-2_16
22Ceschin M., Arrighi L., Longo L., Barbon Junior S. Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest eXplainable Artificial Intelligence, The World Conference (xAI-2025) 2025 Ensemble Learning • Outliers • Explainable Artificial Intelligence • Interpretability • Anomalies • Tree-based Ensemble Model
10.1007/978-3-032-08324-1_12
21Davydko O., Pavlov V., Longo L. A Combination of Integrated Gradients and SRFAMap for Explaining Neural Networks Trained with High-Order Statistical Radiomic Features eXplainable Artificial Intelligence, The World Conference (xAI-2025) 2025 Explainable artificial intelligence • Radiomics • Texture analysis • Medical image processing • Saliency map • Integrated Gradients • Neural Networks • Interpretable Machine Learning
10.1007/978-3-032-08317-3_17
20Kopanja M., Savic M., Longo LEnhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025) 2025 Explainable artificial intelligence • Cost-sensitive decision tree • Surrogate modeling • Rule extraction • Tree-based methods • Model-agnostic explanations • Rule-based systems • Interpretability • Machine Learning.
19Marochko V., Rogala J., Longo L. Integrated Gradients for Enhanced Interpretation of P3b-ERP Classifiers Trained with EEG-superlets in Traditional and Virtual Environments Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025) 2025 Event-related potentials • Deep learning • Convolutional neural networks • Explainable Artificial Intelligence • Integrated Gradients • P3b • Oddball paradigm • time-frequency super-resolution • Superlets.
18Gupta G., Qureshi M.A., Longo L.A Global Post Hoc XAI Method For Interpreting LSTM Using Deterministic Finite State Automata The Irish conference on Artificial Intelligence and Cognitive Science 2025 RNN • interpretability • Explainable AI • LSTM • Deterministic Finite State Automata • k-means clustering • Recurrent Neural Networks
17Marochko V., and Longo L.Enhancing the analysis of the P300 event-related potential with integrated gradients on a convolutional neural network trained with superlets Joint Proceedings of the xAI 2024 Late-breaking Work, Demos and Doctoral Consortium co-located with the 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024) 2024 Event-related potentials • Deep learning • Convolutional neural networks • Explainable Artificial Intelligence • Integrated gradients • P3b • Oddball paradigm • time-frequency super-resolution • Superlets
16Mekonnen E. T., Longo L., Dondio P. Interpreting Black-Box Time Series Classifiers using Parameterised Event Primitives Joint Proceedings of the xAI 2024 Late-breaking Work, Demos and Doctoral Consortium co-located with the 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024) 2024 Explainable Artificial Intelligence • Model-Agnostic • Time Series • Post-hoc • Deep Learning • Machine Learning • Event primitives • Time-series
15Chikkankod A.V., Longo L.A proposal for improving EEG microstate generation via interpretable deep clustering with convolutional autoencoders Joint Proceedings of the xAI 2024 Late-breaking Work, Demos and Doctoral Consortium co-located with the 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024) 2024 EEG Microstates • Shallow clustering • Deep clustering • Convolutional autoencoders • Resting state • Machine Learning • Deep Learning • Microstate theory
14Mekonnen E.T., Longo L., Dondio P.A global model-agnostic rule-based XAI method based on Parameterized Event Primitives for time series classifiers Frontiers Artificial Intelligence 2024 Deep learning • Explainable Artificial Intelligence • time series classification • decision tree • model agnostic • post-hoc • Machine Learning
10.3389/frai.2024.1381921
13Raufi B., Finnegan C., Longo L. A Comparative Analysis of SHAP, LIME, ANCHORS, and DICE for Interpreting a Dense Neural Network in Credit Card Fraud Detection eXplainable Artificial Intelligence, The World Conference (xAI-2024) 2024 Explainable Artificial Intelligence • Credit Card Fraud Detection • Interpretability • methods comparison • SHapley Additive exPlanations • Local Interpretable • Model-agnostic Explanation • ANCHORS • Diverse Counterfactual Explanations
10.1007/978-3-031-63803-9_20
12Davydko O., Pavlov V., Biecek P., & Longo L.SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps eXplainable Artificial Intelligence, The World Conference (xAI-2024) 2024 Explainable artificial intelligence • Radiomics • Texture analysis • Medical image processing • Saliency map • Deep-learning • machine learning
10.1007/978-3-031-63803-9_1
11Hryniewska-Guzik W., Longo L., Biecek P.CNN-Based Explanation Ensembling for Dataset, Representation and Explanations Evaluation eXplainable Artificial Intelligence, The World Conference (xAI-2024) 2024 Explainable Artificial Intelligence • XAI • Convolutional Neural Network • model evaluation • data evaluation • representation learning • ensemble • deep learning • machine learning
10.1007/978-3-031-63797-1_18
10Longo L., Brcic M., Cabitza F., Choi J., Confalonieri R., Del Ser J., Guidotti R., Hayashi Y., Herrera F., Holzinger A., Jiang R., Khosravi H., Lecue F., Malgieri G., Páez A, Samek W., Schneider J, Speith T., Stumpf S.Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions Information Fusion 2024 Explainable artificial intelligence • XAI • Interpretability • Manifesto • Open challenges • Interdisciplinarity • Ethical AI • Large language models • Trustworthy AI • Responsible AI • Generative AI • Multi-faceted explanations • Concept-based explanations • Causality • Actionable XAI • Falsifiability
10.1016/j.inffus.2024.102301
9Sullivan R.S., Longo L. Optimizing Deep Q-Learning Experience Replay with SHAP Explanations: Exploring Minimum Experience Replay Buffer Sizes in Reinforcement Learning Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium, co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) 2023 Deep Reinforcement Learning • Experience Replay • SHapley Additive exPlanations • eXplainable Artificial Intelligence • Machine Learning
8Mekonnen E.T., Dondio P., Longo L. Explaining Deep Learning Time Series Classification Models using a Decision Tree-Based Post-Hoc XAI Method Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) 2023 Explainable Artificial Intelligence • Deep Learning • Time Series • Classification • Decision-Trees • Machine Learning • Post-hoc
7Ahmed T., Longo L.Latent Space Interpretation and Visualisation for Understanding the Decisions of Convolutional Variational Autoencoders Trained with EEG Topographic Maps Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) 2023 Electroencephalography • Convolutional variational autoencoders • latent space interpretation • deep learning • spectral topographic maps • Machine Learning
6Vilone G., Longo L. An Examination of the Effect of the Inconsistency Budget in Weighted Argumentation Frameworks and their Impact on the Interpretation of Deep Neural Networks Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) 2023 Explainable artificial intelligence • Argumentation • Non-monotonic reasoning • Automatic attack extraction • Weighted argumentation frameworks • Inconsistency budget • Machine Learning • Neural Networks
5Davydko O., Pavlov V., Longo L.Selecting textural characteristics of chest X-Rays for pneumonia lesions classification with the integrated gradients XAI attribution method eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Explainable artificial intelligence • Neural networks • Texture analysis • Medical image processing • Classification • Machine Learning
10.1007/978-3-031-44064-9_36
4Natsiou A., O’Leary S., Longo L. An Exploration of the Latent Space of a Convolutional Variational Autoencoder for the Generation of Musical Instrument Tones eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Explainable Artificial Intelligence • Variational Autoencoders • Audio Representations • Audio Synthesis • Latent Feature Importance • Deep Learning • Machine Learning
10.1007/978-3-031-44070-0_24
3Gómez Tapia C., Bozic B., Longo L. Investigating the Effect of Pre-processing Methods on Model Decision-Making in EEG-Based Person Identification eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Electroencephalography • eXplainable Artificial Intelligence • Deep Learning • Signal processing • attribution xAI methods • Graph-Neural Network • Biometrics • signal-to-noise ratio
10.1007/978-3-031-44070-0_7
2Vilone G., Longo L.Development of a Human-Centred Psychometric Test for the Evaluation of Explanations Produced by XAI Methods eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Explainable Artificial Intelligence • Human-centred evaluation • Psychometrics • Machine Learning • Deep Learning • Explainability
10.1007/978-3-031-44070-0_11
1Vilone G. Longo L.A global model-agnostic XAI method for the automatic formation of an abstract argumentation framework and its objective evaluation. 1st Int. Workshop on Argumentation for eXplainable AI (with 9th Int. Conference on Computational Models of Argument, COMMA 2022) 2022 Explainable artificial intelligence • Argumentation • Non-monotonic reasoning • Method evaluation • Metrics of explainability
# Authors Title Details Date Pdf/Links/Bibtex Keywords