These are some of my publications as a researcher in Machine Learning and Natural Language Processing:
Cardellino, C., Collias, T., Molinet, B., Hain, E., Sun, W., Agerri, R., Villata, S., Cabrio, E. “ANTIDOTE: ArgumeNtaTIon-Driven explainable artificial intelligence fOr digiTal mEdicine”. 27TH European Conference on Artificial Intelligence, October 2024, Santiago de Compostela, Spain. [DOI] [PDF]
Cardellino, C., Villata, S., Cabrio, E. “From Political Debates to Deliberative Democracy: A Roadmap to Assess Semi-Supervised Argument Mining with DISPUTool”. DELITE 2024 The First Workshop on Language-driven Deliberation Technology, May 2024, Torino, Italy. [HAL] [PDF]
Cardellino, C., and Carrascosa, R. 2022. “A Study on Title Encoding Methods for E-Commerce Downstream Tasks”. The International FLAIRS Conference Proceedings 35 (May). [DOI] [PDF]
Cardellino, C., and Carrascosa, R. 2021. “A Study on Multiple Tasks for E-Commerce Marketplaces”. The International FLAIRS Conference Proceedings 34 (April). [DOI] [PDF]
Furman, D. A., Marro, S., Cardellino, C., Popa, D. N., & Alonso Alemany, L. (2021). “You can simply rely on communities for a robust characterization of stances”. The International FLAIRS Conference Proceedings, 34. (April). [DOI] [PDF]
Cardellino, C., Alonso Alemany, L., Teruel, M., Villata, S., and Marro, S. “Convolutional ladder networks for Legal NERC and the impact of unsupervised data in better generalizations.” The Thirty-Second International Flairs Conference. 2019. [HAL] [PDF]
Teruel, M., Cardellino, C., Cardellino F., Alonso Alemany, L. and Villata, S., 2018, May. “Increasing Argument Annotation Reproducibility by Using Inter-annotator Agreement to Improve Guidelines”. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). [ACL] [PDF]
Teruel, M., Cardellino, C., Cardellino, F., Alonso Alemany, L., and Villata, S. “Legal text processing within the MIREL project”. In 1st Workshop on Language Resources and Technologies for the Legal Knowledge Graph, p. 42. 2018. [PDF]
Cardellino, C. (2018). “A Study on Semi-Supervised Methods for Spanish Verb Sense Disambiguation”. Doctoral Dissertation, Universidad Nacional de Córdoba. Argentina. [PDF]
Cardellino, C. and Alonso Alemany, L. “Exploring the impact of word embeddings for disjoint semisupervised Spanish verb sense disambiguation”. Inteligencia Artificial, [S.l.], v. 21, n. 61, p. 67-81, mar. 2018. ISSN 1988-3064. [DOI] [PDF]
Cardellino, C., Teruel, M., Alonso Alemany, L. and Villata, S., 2017, June. “A Low-cost, High-coverage Legal Named Entity Recognizer, Classifier and Linker”. In 16th International Conference on Artificial Intelligence and Law (ICAIL-2017). [DOI] [PDF]
Cardellino, C., Teruel, M., Alonso Alemany, L., and Villata, S. “Ontology Population and Alignment for the Legal Domain: YAGO, Wikipedia and LKIF.” In ISWC (Posters, Demos & Industry Tracks). 2017. [HAL] [PDF]
Cardellino, C., Teruel, M., Alonso Alemany, L. and Villata, S., 2017. “Legal NERC with ontologies, Wikipedia and curriculum learning”. EACL 2017, p.254. [ACL] [PDF]
Cardellino, C., Alonso Alemany, L. (2017). “Disjoint semi-supervised spanish verb sense disambiguation using word embeddings”. In XVIII Simposio Argentino de Inteligencia Artificial (ASAI)-JAIIO 46 (Córdoba, 2017). [PDF]
Teruel, M. and Cardellino, C., “In-domain or out-domain word embeddings? A study for Legal Cases”. ESSLLI 2017 Student Session, p.232. [PDF]
Cardellino, C., Milagro Teruel, Laura Alonso Alemany, and Serena Villata. “Learning Slowly To Learn Better: Curriculum Learning for Legal Ontology Population.” In The Thirtieth International Flairs Conference. 2017. [HAL] [PDF]
Cardellino, C., Villata, S., Alonso Alemany, L. and Cabrio, E., 2015, April. “Information extraction with active learning: A case study in legal text”. In Proceedings of the 16th International Conference on Intelligence Text Processing and Computational Linguistics (CICLing 2015). [HAL] [PDF]
Cardellino, C., Villata, S., Gandon, F., Governatori, G., Lam, H.P. and Rotolo, A., 2014, October. “Licentia: a tool for supporting users in data licensing on the web of data”. In Proceedings of the 2014 International Conference on Posters & Demonstrations Track-Volume 1272 (pp. 277-280). [DOI] [PDF]