Publications

33
Total
16
Journals
7
Conferences
6
Workshops
1
Books
3
Chapters
2025
12
2024
6
2023
5
2022
4
2021
4
2020
1
2019
1

Journals

  1. R. Cantini, M. Capalbo, and D. Talia, “ZEP-NAS: Enabling green-aware model design via zero-cost emission proxy in neural architecture search”, Array, p. 100566, 2025.
  2. R. Cantini, F. Marozzo, A. Orsino, D. Talia, and P. Trunfio, “Dynamic hashtag recommendation in social media with trend shift detection and adaptation”, Transactions on Computational Social Systems, 2025.
  3. R. Cantini, A. Orsino, M. Ruggiero, and D. Talia, “Benchmarking adversarial robustness to bias elicitation in large language models: scalable automated assessment with llm-as-a-judge”, Machine Learning, vol. 114, no. 11, p. 249, 2025.
  4. L. Belcastro, R. Cantini, F. Marozzo, D. Talia, and P. Trunfio, “Detecting mental disorder on social media: a ChatGPT-augmented explainable approach”, Online Social Networks and Media, vol. 48, p. 100321, 2025.
  5. R. Cantini, C. Cosentino, F. Marozzo, D. Talia, and P. Trunfio, “Harnessing prompt-based large language models for disaster monitoring and automated reporting from social media feedback”, Online Social Networks and Media, vol. 45, p. 100295, 2025.
  6. R. Cantini, C. Cosentino, I. Kilanioti, F. Marozzo, and D. Talia, “Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media”, Machine Learning, vol. 114, no. 1, p. 13, 2025.
  7. R. Cantini, A. Orsino, and D. Talia, “Xai-driven knowledge distillation of large language models for efficient deployment on low-resource devices”, Journal of Big Data, vol. 11, no. 1, 2024.
  8. R. Cantini, F. Marozzo, A. Orsino, et al., “Block size estimation for data partitioning in hpc applications using machine learning techniques”, Journal of Big Data, vol. 11, no. 1, 2024.
  9. L. Belcastro, R. Cantini, F. Marozzo, A. Orsino, D. Talia, and P. Trunfio, “Programming big data analysis: principles and solutions”, Journal of Big Data, vol. 9, no. 1, 2022.
  10. R. Cantini, F. Marozzo, D. Talia, and P. Trunfio, “Analyzing political polarization on social media by deleting bot spamming”, Big Data and Cognitive Computing, vol. 6, no. 1, 2022.
  11. L. Belcastro, F. Branda, R. Cantini, F. Marozzo, D. Talia, and P. Trunfio, “Analyzing voter behavior on social media during the 2020 us presidential election campaign”, Social Network Analysis and Mining, vol. 12, no. 1, 2022.
  12. L. Belcastro, R. Cantini, and F. Marozzo, “Knowledge discovery from large amounts of social media data”, Applied Sciences, vol. 12, no. 3, 2022.
  13. R. Cantini, F. Marozzo, G. Bruno, and P. Trunfio, “Learning sentence-to-hashtags semantic mapping for hashtag recommendation on microblogs”, ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 16, no. 2, 2021.
  14. R. Cantini, F. Marozzo, S. Mazza, D. Talia, and P. Trunfio, “A weighted artificial bee colony algorithm for influence maximization”, Online Social Networks and Media, vol. 26, p. 100167, 2021.
  15. R. Cantini, F. Marozzo, A. Orsino, D. Talia, and P. Trunfio, “Exploiting machine learning for improving in-memory execution of data-intensive workflows on parallel machines”, Future Internet, vol. 13, no. 5, 2021.
  16. L. Belcastro, R. Cantini, F. Marozzo, D. Talia, and P. Trunfio, “Learning political polarization on social media using neural networks”, IEEE Access, vol. 8, 2020.

Conferences

  1. R. Cantini, C. Cosentino, F. Marozzo, D. Talia, and P. Trunfio, “Neural topic modeling in social media by clustering latent hashtag representations”, in ECAI 2025, 2025.
  2. R. Cantini, G. Cosenza, A. Orsino, and D. Talia, “Are large language models really bias-free? jailbreak prompts for assessing adversarial robustness to bias elicitation”, in Discovery Science, 2024.
  3. R. Cantini, C. Cosentino, and F. Marozzo, “Multi-dimensional classification on social media data for detailed reporting with large language models”, in AIAI, 2024.
  4. R. Cantini, C. Cosentino, I. Kilanioti, F. Marozzo, and D. Talia, “Unmasking covid-19 false information on twitter: a topic-based approach with bert”, in Discovery Science, 2023.
  5. R. Cantini and F. Marozzo, “Topic detection and tracking in social media platforms”, in Pervasive Knowledge and Collective Intelligence on Web and Social Media, 2023.
  6. R. Cantini, F. Marozzo, A. Orsino, M. Passarelli, and P. Trunfio, “A visual tool for reducing returns in e-commerce platforms”, in IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), 2021.
  7. L. Belcastro, R. Cantini, F. Marozzo, D. Talia, and P. Trunfio, “Discovering political polarization on social media: a case study”, in 15th International Conference on Semantics, Knowledge and Grids (SKG), 2019.

Workshops

  1. R. Cantini, N. Gabriele, A. Orsino, and D. Talia, “Is reasoning all you need? probing bias in the age of reasoning language models,” AEQUITAS Workshop (ECAI 2025), 2025. To appear.
  2. R. Cantini, N. Gabriele, and A. Orsino, “A parameter-efficient approach to distilling large language models via meta-learning”, in ADBIS, 2025.
  3. L. Belcastro, R. Cantini, F. Marozzo, A. Orsino, D. Talia, and P. Trunfio, “Advancing green and fair ai: a research perspective on environmental and social sustainability”, Ital-IA 2025.
  4. R. Cantini, D. M. Longo, and D. Thakur, “Preface to the proceedings of green-aware ai 2024”, AIxIA 2024.
  5. R. Cantini, A. Orsino, D. Talia, and P. Trunfio, “Towards interpretable energy estimation for edge ai applications”, IPDPS 2025.
  6. P. Lindia, R. Cantini, F. Bettucci, L. Sartori, and P. Trunfio, “Enhancing the evaluation of fault detection models in smart agriculture using llm agents for rule-based anomaly generation”, AIxIA 2024.

Books

  1. D. Talia, P. Trunfio, F. Marozzo, L. Belcastro, R. Cantini, and A. Orsino, “Programming big data applications: scalable tools and frameworks for your needs”, World Scientific, 2023.

Chapters

  1. L. Belcastro, R. Cantini, F. Marozzo, D. Talia, and P. Trunfio, “Shedding light inside the black box: techniques for explainable artificial intelligence in healthcare”, in Explainable Machine Intelligence in Healthcare, 2025.
  2. R. Cantini, F. Marozzo, and A. Orsino, “Deep learning meets smart agriculture: using lstm networks to handle anomalous and missing sensor data in the compute continuum”, in Device-Edge-Cloud Continuum, 2023.
  3. A. Orsino, R. Cantini, and F. Marozzo, “Evaluating the performance of a multimodal speaker tracking system at the edge-to-cloud continuum”, in Device-Edge-Cloud Continuum, 2023.