Francesco BUSOLIN

Qualifica
Assegnista
E-mail
francesco.busolin@unive.it
851884@stud.unive.it
Sito web
www.unive.it/persone/francesco.busolin (scheda personale)
Struttura
Dipartimento di Scienze Ambientali, Informatica e Statistica
Sito web struttura: https://www.unive.it/dais

Busolin F.; Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Trani S.; Veneri A. Efficient Re-ranking with Cross-encoders via Early Exit , SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES, Association for Computing Machinery, Inc, pp. 2534-2544, Convegno: 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, 2025
DOI 2025, Articolo in Atti di convegno - Scheda ARCA: 10278/5112007


Francesco Busolin;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando;Raffaele Perego;Salvatore Trani Early Exit Strategies for Approximate k-NN Search in Dense Retrieval in Francesco Busolin; Claudio Lucchese; Franco Maria Nardini; Salvatore Orlando; Raffaele Perego; Salvatore Trani, CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, New York, Association for Computing Machinery, pp. 3647-3652, Convegno: CIKM '24: The 33rd ACM International Conference on Information and Knowledge Management, 21/10/2024-25/10/2024 (ISBN 979-8-4007-0436-9)
DOI - URL correlato 2024, Articolo in Atti di convegno - Scheda ARCA: 10278/5081787


Busolin, Francesco; Lucchese, Claudio; Nardini, Franco Maria; Orlando, Salvatore; Perego, Raffaele; Trani, Salvatore Early Exit Strategies for Learning-to-Rank Cascades in IEEE ACCESS, vol. Online (ISSN 2169-3536)
DOI 2023, Articolo su rivista - Scheda ARCA: 10278/5043380


Busolin F.; Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Trani S. Learning Early Exit Strategies for Additive Ranking Ensembles , SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Association for Computing Machinery, Inc, pp. 2217-2221, Convegno: 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021, 2021 (ISBN 9781450380379)
DOI 2021, Articolo in Atti di convegno - Scheda ARCA: 10278/3743016