Education
- Master’s degree in Scienze del Testo per le Professioni Digitali (LM-43), Università di Catania, 2021.
- Thesis Title: A Large Visual Question Answering Dataset for Italian Cultural Heritage.
- Vote: 110/110 cum laude.
- Bachelor’s degree in Lingue e culture europee, euroamericane ed orientali (L-11), 2019.
- Thesis Title: Il mito di Prometeo tra tecnica e cultura: Leopardi, Shelley, Goethe.
- Vote: 103/110.
Employment History
- 16/03/2022 - 29/10/2022, Research Assistent, Istituto di Scienze e Tecnologie della Cognizione - Consiglio Nazionale delle Ricerche (ISTC-CNR), Rome, Italy.
- Research program: Machine-reading for knowledge engineering: study, design and development of methods and theories for the creation of knowledge graphs from textual corpora through the machine-reading paradigm.
- 08/04/2021 - 08/10/2021, Research contract, Istituto di Scienze e Tecnologie della Cognizione - Consiglio Nazionale delle Ricerche (ISTC-CNR), Catania, Italy.
My research lies in Natural Language Processing (NLP) and Machine Learning, with a specific focus on human-centered AI. Additionally, my work explores the integration of NLP and the Semantic Web, delving into the use of Knowledge Graphs and their integration with machine learning models to enhance knowledge representation and management.
Journal Papers
- C. F. Longo, M. Mongiovı, L. Bulla, and A. Lieto, “Eliciting metaknowledge in large language models”. Cognitive Systems Research, 2025, under publication.
- L. Bulla, S. De Giorgis, M. Mongiovı, and A. Gangemi, “Large language models meet moral values: A comprehensive assessment of moral abilities,” Computers in Human Behavior Reports, p. 100 609, 2025.
- L. Bulla, A. Midolo, M. Mongiovı, and E. Tramontana, “Ex-code: A robust and explainable model to detect ai-generated code,” Information, vol. 15, no. 12, p. 819, 2024.
- F. Becattini, P. Bongini, L. Bulla, et al., “Viscounth: A large-scale multilingual visual question answering dataset for cultural heritage,” ACM Transactions on Multimedia Computing, Communications and Applications, 2023.
- D. Golinelli, A. G. Nuzzolese, F. Sanmarchi, et al., “Semi-automatic systematic literature reviews and information extraction of covid-19 scientific evidence: Description and preliminary results of the coke project”, Information, vol. 13, no. 3, p. 117, 2022.
Conference Proceedings
- L. Bulla and M. Mongiovı, “Underperformance or pluralism: A machine learning perspective on inter-annotator agreement,” in The Fourth International Conference Series on Hybrid Human Artificial Intelligence (HHAI), 2025, under publication.
- L. Bulla and M. Mongiovı, “Adequate prompting improves performance of regression models of emotional content,” in Proceedings of the 2024 International Conference on Information Technology for Social Good, 2024, pp. 135–142.
- C. Longo, M. Mongiovi, L. Bulla, and G. Tuccari, “Htc-gen: A generative llm-based approach to handle data scarcity in hierarchical text classification,” in Proceedings of the 13th International Conference on Data Science, Technology and Applications. Dijon, France: SCITEPRESS-Science and Technology Publications, 2024, pp. 129–138.
- L. Bulla, S. De Giorgis, A. Gangemi, C. Lucifora, and M. Mongiovı, “Comparing user perspectives in a virtual reality cultural heritage environment,” in International Conference on Advanced Information Systems Engineering, Springer, 2023, pp. 3–15.
- L. Bulla, A. Gangemi, et al., “Towards distribution-shift robust text classification of emotional content,” in Findings of the Association for Computational Linguistics: ACL 2023, 2023, pp. 8256–8268.
- L. Bulla, S. D. Giorgis, A. Gangemi, L. Marinucci, and M. Mongiovı, “Detection of morality in tweets based on the moral foundation theory,” in International Conference on Machine Learning, Optimization, and Data Science, Springer, 2022, pp. 1–13.
- L. Asprino, L. Bulla, L. Marinucci, M. Mongiovı, and V. Presutti, “A large visual question answering dataset for cultural heritage,” in International Conference on Machine Learning, Optimization, and Data Science, Springer, 2021, pp. 193–197.
Workshop Proceedings
- M. Boscariol, L. Bulla, L. Draetta, B. Fiumanò, E. Lenzi, and L. Piano, “Evaluation of llms on long-tail entity linking in historical documents,” in Proceedings of eXtraction and eXploitation of long-TAIL Knowledge with LLMs and KGs (X-TAIL), 2025.
- L. Bulla, A. Gangemi, and M. Mongiovı, “Do language models understand morality? towards a robust detection of moral content,” in International Workshop on Value Engineering in AI, 2023, pp. 98–113.
- L. Bulla and M. Mongiovı, “Istc-cnr at emotivita: Towards better dimensional and multi-dimensional analysis of vad emotions,” in 2023.
- L. Asprino, L. Bulla, S. De Giorgis, A. Gangemi, L. Marinucci, and M. Mongiovı, “Uncovering values: Detecting latent moral content from natural language with explainable and non-trained methods,” in Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, 2022, pp. 33–41.
- L. Bulla, M. C. Frangipane, M. L. Mancinelli, et al., “Developing and aligning a detailed controlled vocabulary for artwork,” in European Conference on Advances in Databases and Information Systems, 2022, pp. 529–541.
