# Authors Title Details Date Pdf/Links/Bibtex Keywords
27El-Qoraychy FZ, Mualla Y., Zhao H., Dridi M., Créput JC, Longo L. Explainable AI for sign language recognition models: Integrating Grad-Cam LIME and Integrated Gradients Plos One 2025 Sign language • Machine Learning • Explainable Artificial Intelligence • Grad-Cam • Lime • Integrated Gradients
10.1371/journal.pone.0336481
26Ephrem 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
25Ahmed 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
24Ceschin 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
23Davydko 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
22Longo L., Berretta S., Verda D., Rizzo L.Computational argumentation and automatic rule-generation for explainable data-driven modeling IEEE Access 2025 Rule-base systems • Explainable Artificial Intelligence • Logic Learning Machine • Non-monotonic reasoning • Defeasible Reasoning • Explainability • Computational argumentation • Argumentation semantics • Explainability
10.1109/ACCESS.2025.3618992
21Kopanja 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.
20Marochko 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.
19Criscuolo S., Giugliano S., Apicella, A., Donnarumma F., Amato F. Tedesco A., Longo L.Exploring the Latent Space of Person-Specific Convolutional Autoencoders for Eye-Blink Artefact Mitigation in EEG Signals 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI) 2024 Electroencephalography • Autoencoders • Eye-blink Artefacts Detection • Latent Space interpretation • Explainable Artificial Intelligence • Artificial Intelligence • Machine Learning • Deep learning
10.1109/RTSI61910.2024.10761377
18Marochko 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
17Mekonnen 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
16Chikkankod 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
15Mekonnen 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
14Rizzo L., Verda D., Berretta S., Longo L. A Novel Integration of Data-Driven Rule Generation and Computational Argumentation for Enhanced Explainable AI Machine Learning and Knowledge Extraction 2024 rule-base AI • explainable artificial intelligence • computational argumentation • defeasible reasoning • Artificial Intelligence
10.3390/make6030101
13Sullivan 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
12Mekonnen 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
11Ahmed 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
10Vilone 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
9Davydko 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
8Natsiou 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
7Gómez 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
6O’ Sullivan R., Longo LExplaining Deep Q-Learning Experience Replay with SHapley Additive exPlanations Machine Learning and Knowledge Extraction 2023 Deep Reinforcement Learning • Experience Replay • SHapley Additive exPlanations • eXplainable Artificial Intelligence • Artificial Intelligence
10.3390/make5040072
5Vilone G., Longo L.A Novel Human-Centred Evaluation Approach and an Argument-Based Method for Explainable Artificial Intelligence. Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference 2022 Explainable Artificial Intelligence • Argumentation • Human-centred evaluation • Non-monotonic reasoning • Explainability
10.1007/978-3-031-08333-4_36
4Vilone G., Longo L.Classification of Explainable Artificial Intelligence Methods through Their Output Formats Machine Learning and Knowledge Extraction 2021 explainable artificial intelligence • method classification • systematic literature review
10.3390/make3030032
3Vilone G, Longo L.Notions of explainability and evaluation approaches for explainable artificial intelligence Information fusion 2021 Explainable artificial intelligence • Notions of explainability • Evaluation methods
10.1016/j.inffus.2021.05.009
2Vilone G., Rizzo L., Longo L.A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence Proceedings for the 28th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, December 7-8, 2020 2020 Explainable artificial intelligence • Rule extraction • Method • comparison • evaluation
1Rizzo L., Longo L.A Qualitative Investigation of the Explainability of Defeasible Argumentation and Non-Monotonic Fuzzy Reasoning 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science 2018 Defeasible Argumentation • Non-monotonic Reasoning • Fuzzy Reasoning • Argumentation Theory • Explainable Artificial Intelligence • Artificial Intelligence • Modeling
# Authors Title Details Date Pdf/Links/Bibtex Keywords