Per Year

 @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
}