| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 2 | Vilone 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 | @InProceedings{ViloneLongo2025, author="Vilone, Giulia and Longo, Luca", editor="Guidotti, Riccardo and Schmid, Ute and Longo, Luca", title="Evaluating Argumentation Graphs as Global Explainable Surrogate Models for Dense Neural Networks and Their Comparison with Decision Trees", booktitle="Explainable Artificial Intelligence", year="2026", publisher="Springer Nature Switzerland", address="Cham", pages="89--112", isbn="978-3-032-08333-3" } [Close]
| 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 |
| 1 | Kopanja M., Savic M., Longo L | Enhancing 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 |
@inproceedings{, title={Enhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation}, author={Kopanja, Marija and Savi?, Miloš and Longo, Luca}, year={2025}, booktitle = {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), Istanbul, Turkey, 9-11 July, 2025}, publisher = {CEUR-WS.org}, volume = {4017}, series = {{CEUR} Workshop Proceedings}, editor = {Przemys?aw Biecek, Slawomir Nowaczyk, Gitta Kutyniok, Luca Longo}, pages={129-136}, url={https://ceur-ws.org/Vol-4017/paper_17.pdf} } [Close]
| Explainable artificial intelligence • Cost-sensitive decision tree • Surrogate modeling • Rule extraction • Tree-based
methods • Model-agnostic explanations • Rule-based systems • Interpretability • Machine Learning. |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |