Per anno

@inproceedings{llmbasedhealthcarechatbots-telmed2024,
 author={Montagna, Sara and Aguzzi, Gianluca and Ferretti, Stefano and Pengo, Martino Francesco and Klopfenstein, Lorenz Cuno and Ungolo, Michelangelo and Magnini, Matteo},
 booktitle={2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)},
keywords = {large language model, medical chatbot, chronic disease management},
 title={LLM-based Solutions for Healthcare Chatbots: a Comparative Analysis},
 year={2024},
 volume={},
 number={},
 pages={346-351},
 keywords={Pervasive computing;Privacy;Filtering;Conferences;Computational modeling;Medical services;Chatbots;Large Language Model;Medical Chatbot;Chronic Disease Management},
 doi={10.1109/PerComWorkshops59983.2024.10503257}}

@inproceedings{skemetrics-aaai2023,
   address = {San Francisco, California},
   author = {Sabbatini, Federico and Calegari, Roberta},
   booktitle = {AAAI 2023 Spring Symposium Series},
   keywords = {Explainable artificial intelligence; Symbolic knowledge extraction; Readability metrics; AutoML},
   month = mar,
   title = {On the Evaluation of the Symbolic Knowledge Extracted from Black Boxes},
   year = 2023
}

@article{skeislr-acmcs,
   acm = {3645103},
   articleno = 161,
   author = {Ciatto, Giovanni and Sabbatini, Federico and Agiollo, Andrea and Magnini, Matteo and Omicini, Andrea},
   doi = {10.1145/3645103},
   eissn = {1557-734},
   iris = {11585/969235},
   issn = {0360-0300},
   journal = {ACM Computing Surveys},
   keywords = {Logic; Machine learning theory; Hybrid symbolic-numeric methods; Knowledge representation and reasoning},
   month = jun,
   number = 6,
   numpages = 35,
   pages = {161:1--161:35},
   publisher = {ACM},
   scholar = {13701373869146776438},
   scopus = {2-s2.0-85188835517},
   semanticscholar = {267611660},
   title = {Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review},
   url = {https://dl.acm.org/doi/10.1145/3645103},
   urlopenaccess = {https://dl.acm.org/doi/pdf/10.1145/3645103},
   urlpdf = {https://dl.acm.org/doi/pdf/10.1145/3645103},
   volume = 56,
   year = 2024
}

@article{ndnfl-fgcs2023,
   author = {Agiollo, Andrea and Enkeleda Bardhi and Mauro Conti and Nicolò Dal Fabbro and Riccardo Lazzeretti},
   doi = {10.1016/j.future.2023.11.009},
   issn = {0167-739X},
   journal = {Future Generation Computer Systems},
   keywords = {Anonymous communication, Federated Learning, Named Data Networking, Privacy-preserving},
   pages = {288--303},
   publisher = {Elsevier},
   note = {Special Issue on Federated Learning on the Edge: Challenges and Future Directions},
   title = {Anonymous Federated Learning via Named-Data Networking},
   url = {https://www.sciencedirect.com/science/article/pii/S0167739X23004144},
   volume = 152,
   year = 2024
}

@article{eneafl-fgcs154,
   author = {Agiollo, Andrea and Bellavista, Paolo and Mendula, Matteo and Omicini, Andrea},
   doi = {10.1016/j.future.2024.01.007},
   editor = {Hao Wu and Carlo Puliafito and Omer F. Rana and Luiz F. Bittencourt},
   iris = {11585/953081},
   issn = {0167-739X},
   journal = {Future Generation Computer Systems},
   keywords = {Serverless, Federated Learning, Energy Management, Internet of Things, Resource-constrained Learning},
   month = may,
   note = {Special Issue ``Serverless Computing in the Cloud-to-Edge Continuum''},
   numpages = 16,
   pages = {219--234},
   publisher = {Elsevier Science B.V.},
   scholar = {15164122000920541506},
   scopus = {2-s2.0-85182399653},
   title = {{EneA-FL}: Energy-aware Orchestration for Serverless Federated Learning},
   url = {https://www.sciencedirect.com/science/article/pii/S0167739X24000074},
   volume = 154,
   wos = {WOS:001164533000001},
   year = 2024
}