Giovanni Puccetti, Anna Rogers, Chiara Alzetta, Felice Dell’Orletta, and Andrea Esuli. “AI ‘News’ Content Farms Are Easy to Make and Hard to Detect: A Case Study in Italian”. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Ed. by Lun-Wei Ku, Andre Martins, and Vivek Srikumar. Bangkok, Thailand: Association for Computational Linguistics, Aug. 2024, pp. 15312–15338. URL: https://aclanthology.org/2024.acl-long.817.
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, Alham Aji, Nizar Habash, Iryna Gurevych, and Preslav Nakov. “M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection”. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Ed. by Lun-Wei Ku, Andre Martins, and Vivek Srikumar. Bangkok, Thailand: Association for Computational Linguistics, Aug. 2024, pp. 3964- 3992. URL: https://aclanthology.org/2024.acl-long.218
Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, and Thomas Arnold. “SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection”. In: Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024). Ed. by Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, and Aiala Rosá. Mexico City, Mexico: Association for Computational Linguistics, June 2024, pp. 20572079. DOI: 10.18653/v1/2024.semeval-1.279.
Giovanni Puccetti, Vito Giordano, Irene Spada, Filippo Chiarello, Gualtiero Fantoni, "Technology identification from patent texts: A novel named entity recognition method". In:Technological Forecasting and Social Change, Volume 186, Part B, 2023, 122160, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2022.122160. (https://www.sciencedirect.com/science/article/pii/S0040162522006813)
Giovanni Puccetti and Andrea Esuli. “AIMH at MULTI-Fake-DetectIVE: System Report”. In: Proceedings of the 8th Workshop on the Evaluation of Natural Language and Speech Tools for Italian (EVALITA 2023). Parma, IT, 2023. URL: https://api.semanticscholar.org/CorpusID:261529509
Vito Giordano, Giovanni Puccetti, Filippo Chiarello, Tommaso Pavanello, and Gualtiero Fantoni. “Unveiling the inventive process from patents by extracting problems, solutions and advantages with natural language processing”. In: Expert Systems with Applications 229 (2023), p. 120499. ISSN: 0957-4174. DOI: 10.1016/j.eswa.2023.120499
Giovanni Puccetti, Anna Rogers, Aleksandr Drozd and Felice Dell'Orletta. "Outlier Dimensions that Disrupt Transformers are Driven by Frequency" To appear in: Findings of EMNLP 2022. Abhu Dabi, December 7-11, 2022. URL: https://arxiv.org/abs/2205.11380.
Giovanni Puccetti, Alessio Miaschi, and Felice Dell’Orletta. “How Do BERT Embeddings Organize Linguistic Knowledge?” In:Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures. Online: Association for Computational Linguistics, June 2021,pp. 48–57. DOI:10.18653/v1/2021.deelio-1.6. URL:https://aclanthology.org/2021.deelio-1.6.
Giovanni Puccetti, Filippo Chiarello, and Gualtiero Fantoni. “A simple and fast method for Named Entity context extraction from patents”. In:Expert Systems with Applications 184 (2021), p. 115570.ISSN: 0957-4174. DOI:https://doi.org/10.1016/j.eswa.2021.115570. URL:https://www.sciencedirect.com/science/article/pii/S0957417421009751.
Giovanni Puccetti, Luis Bolanos, Filippo Chiarello, and Gualtiero Fantoni. B4DS @ PRELEARN: Ensemble Method for Prerequisite Learning (short paper). In: Proceedings of the Seventh Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2020), Online event, December 17th, 2020. Ed. by Valerio Basile et al. Vol. 2765. CEUR Workshop Proceedings. CEUR-WS.org, 2020. URL: http://ceur-ws.org/Vol-2765/paper107.pdf.