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LIGA Davide

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

Main Referenced Co-authors
Palmirani, Monica (10)
MARKOVICH, Réka  (3)
PASETTO, Luca  (2)
Amitrano, Daniele (1)
Bentzen, Bruno (1)
Main Referenced Keywords
Argument Mining (5); AI&Law (4); Argument schemes (3); Argumentation schemes (3); Legal Knowledge Representation (3);
Main Referenced Disciplines
Computer science (22)

Publications (total 22)

The most downloaded
94 downloads
LIGA, D., & PASETTO, L. (2023). Testing spatial reasoning of Large Language Models: the case of tic-tac-toe [Paper presentation]. AIxPAC, Rome, Italy. https://hdl.handle.net/10993/57922

The most cited

10 citations (Scopus®)

Liga, D. (2019). Argumentative evidences classification and argument scheme detection using tree kernels. In Proceedings of the 6th Workshop on Argument Mining (pp. 92-97). doi:10.18653/v1/W19-4511 https://hdl.handle.net/10993/52145

LIGA, D., & ROBALDO, L. (November 2023). Fine-tuning GPT-3 for legal rule classification. Computer Law & Security Review, 51, 105864. doi:10.1016/j.clsr.2023.105864
Editorial reviewed

LIGA, D., & PASETTO, L. (2023). Testing the reasoning of Large Language Models on tic-tac-toe [Paper presentation]. ACLAI 2023.
Peer reviewed

LIGA, D. (2023). The Interplay Between Lawfulness and Explainability in the Automated Decisionmaking of the EU Administration. SSRN Electronic Journal. doi:10.2139/ssrn.4561012
Peer reviewed

LIGA, D., MARKOVICH, R., & Fidelangeli, A. (2023). OntoVAT, an ontology for knowledge extraction in VAT-related judgments [Paper presentation]. JURISIN 2023, Kumamoto, Japan.
Peer reviewed

LIGA, D., MARKOVICH, R., & Amitrano, D. (2023). PaTrOnto, an ontology for patents and trademarks [Paper presentation]. JURISIN 2023, Kumamoto, Japan.
Peer reviewed

LIGA, D., Bentzen, B., Liao, B., MARKOVICH, R., Xiong, M., Wei, B., & Xu, T. (Eds.). (2023). Logics for AI and Law: Joint Proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law, September 8-9 and 11-12, 2023, Hangzhou. Hangzhou, China: College Publications.
Editorial reviewed

LIGA, D. (2023). The Argumentation Scheme from Vicarious Liability [Paper presentation]. JURISIN 2023, Kumamoto, Japan.
Peer reviewed

LIGA, D., & PASETTO, L. (2023). Testing spatial reasoning of Large Language Models: the case of tic-tac-toe [Paper presentation]. AIxPAC, Rome, Italy.
Peer reviewed

Liga, D., & Palmirani, M. (2022). Deontic Sentence Classification Using Tree Kernel Classifiers. In Intelligent Systems and Applications (pp. 54-73). Springer, Cham.
Peer reviewed

Liga, D. (2022). Hybrid Artificial Intelligence to extract patterns and rules from argumentative and legal texts [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52142

Palmirani, M., & Liga, D. (2022). Derogations Analysis of European Legislation Through Hybrid AI Approach. In Electronic Government and the Information Systems Perspective: 11th International Conference, EGOVIS 2022 (pp. 123-137). Springer, Cham.
Peer reviewed

Liga, D., & Palmirani, M. (2022). Transfer Learning for Deontic Rule Classification: the Case Study of the GDPR. In INTERNATIONAL CONFERENCE ON LEGAL KNOWLEDGE AND INFORMATION SYSTEMS, Saarbrücken 14-16 December 2022. EasyChair.
Peer reviewed

Palmirani, M., Sovrano, F., Liga, D., Sapienza, S., & Vitali, F. (2021). Hybrid AI Framework for Legal Analysis of the EU Legislation Corrigenda. In Legal Knowledge and Information Systems (pp. 68-75). IOS Press. doi:10.3233/FAIA210319
Peer reviewed

Liga, D., & Palmirani, M. (2020). Uncertainty in Argumentation Schemes: Negative Consequences and Basic Slippery Slope. In Logic and Argumentation (pp. 259-278). Springer, Cham. doi:10.1007/978-3-030-44638-3_16
Peer reviewed

Liga, D., & Palmirani, M. (2020). Transfer Learning with Sentence Embeddings for Argumentative Evidence Classification. In Proceedings of the 20th Workshop on Computational Models of Natural Argument (pp. 11). CEUR-WS.org Sun SITE Central Europe.
Peer reviewed

Liga, D., & Palmirani, M. (2020). Argumentation Schemes as Templates? Combining Bottom-up and Top-down Knowledge Representation. In Proceedings of the 20th Workshop on Computational Models of Natural Argument (pp. 51). 56.
Peer reviewed

Liga, D., & Palmirani, M. (2020). Combining tree kernels and tree representations to classify argumentative stances. In Advances in Semantics and Linked Data: Joint Workshop Proceedings from ISWC 2020 (pp. 12-23).
Peer reviewed

Liga, D., & Palmirani, M. (2019). Detecting “slippery slope” and other argumentative stances of opposition using tree kernels in monologic discourse. In International Joint Conference on Rules and Reasoning (pp. 180-189). Springer, Cham. doi:10.1007/978-3-030-31095-0_13
Peer reviewed

Liga, D., & Palmirani, M. (2019). Classifying argumentative stances of opposition using Tree Kernels. In ACAI 2019: Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence. doi:10.1145/3377713.3377717
Peer reviewed

Liga, D. (2019). Argumentative evidences classification and argument scheme detection using tree kernels. In Proceedings of the 6th Workshop on Argument Mining (pp. 92-97). doi:10.18653/v1/W19-4511
Peer reviewed

Liga, D. (2019). Comparing Tree Kernels performances in argumentative evidence classification. In CLADAG 2019 - Book of Short Papers.
Peer reviewed

Ruoto, A., Santarcangelo, V., Liga, D., Oddo, G., Giacalone, M., & Iorio, E. (2017). The Sentiment of the infosphere: a sentiment analysis approach for the big conversation on the net. In Data science and social research (pp. 215-222). Springer, Cham. doi:10.1007/978-3-319-55477-8_20
Peer reviewed

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