Follow
Francesco Sovrano
Title
Cited by
Cited by
Year
Deep learning based multi-label text classification of UNGA resolutions
F Sovrano, M Palmirani, F Vitali
Proceedings of the 13th international conference on theory and practice of …, 2020
232020
Legal knowledge extraction for knowledge graph based question-answering
F Sovrano, M Palmirani, F Vitali
Legal Knowledge and Information Systems, 143-153, 2020
152020
Crawling in rogue’s dungeons with (partitioned) a3c
A Asperti, D Cortesi, F Sovrano
Machine Learning, Optimization, and Data Science: 4th International …, 2019
122019
Modelling GDPR-compliant explanations for trustworthy AI
F Sovrano, F Vitali, M Palmirani
Electronic Government and the Information Systems Perspective: 9th …, 2020
112020
From Philosophy to Interfaces: An Explanatory Method and a Tool Inspired by Achinstein’s Theory of Explanation
F Sovrano, F Vitali
26th International Conference on Intelligent User Interfaces, 81-91, 2021
92021
Metrics, explainability and the European AI act proposal
F Sovrano, S Sapienza, M Palmirani, F Vitali
J 5 (1), 126-138, 2022
82022
Combining experience replay with exploration by random network distillation
F Sovrano
2019 IEEE conference on games (CoG), 1-8, 2019
82019
Hybrid refining approach of pronto ontology
M Palmirani, G Bincoletto, V Leone, S Sapienza, F Sovrano
Electronic Government and the Information Systems Perspective: 9th …, 2020
72020
The Difference between Explainable and Explaining: Requirements and Challenges under the GDPR.
F Sovrano, F Vitali, M Palmirani
XAILA@ jurix, 2019
72019
Crawling in Rogue's Dungeons With Deep Reinforcement Techniques
A Asperti, D Cortesi, C De Pieri, G Pedrini, F Sovrano
IEEE Transactions on Games 12 (2), 177-186, 2019
72019
An objective metric for explainable AI: how and why to estimate the degree of explainability
F Sovrano, F Vitali
arXiv preprint arXiv:2109.05327, 2021
62021
Making things explainable vs explaining: Requirements and challenges under the GDPR
F Sovrano, F Vitali, M Palmirani
AI Approaches to the Complexity of Legal Systems XI-XII: AICOL International …, 2021
62021
A Survey on Methods and Metrics for the Assessment of Explainability under the Proposed AI Act
F Sovrano, S Sapienza, M Palmirani, F Vitali
Legal Knowledge and Information Systems: JURIX 2021: The Thirty-fourth …, 2022
52022
PrOnto ontology refinement through open knowledge extraction
M Palmirani, G Bincoletto, V Leone, S Sapienza, F Sovrano
Legal Knowledge and Information Systems, 205-210, 2019
42019
Explanation-aware experience replay in rule-dense environments
F Sovrano, A Raymond, A Prorok
IEEE Robotics and Automation Letters 7 (2), 898-905, 2021
32021
Generating User-Centred Explanations via Illocutionary Question Answering: From Philosophy to Interfaces
F Sovrano, F Vitali
ACM Trans. Interact. Intell. Syst., 2021
32021
A modular deep-learning environment for rogue
A Asperti, C De Pieri, M Maldini, G Pedrini, F Sovrano
WSEAS Trans. Syst. Control 12, 362-373, 2017
32017
How to Quantify the Degree of Explainability: Experiments and Practical Implications
F Sovrano, F Vitali
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-9, 2022
22022
Combining shallow and deep learning approaches against data scarcity in legal domains
F Sovrano, M Palmirani, F Vitali
Government Information Quarterly 39 (3), 101715, 2022
22022
A dataset for evaluating legal question answering on private international law
F Sovrano, M Palmirani, B Distefano, S Sapienza, F Vitali
Proceedings of the Eighteenth International Conference on Artificial …, 2021
22021
The system can't perform the operation now. Try again later.
Articles 1–20