Luana BULLA

Dottorando
Dottorato in Informatica - Ciclo 38°
Tutor: Misael MONGIOVI'

Formazione

  • Laurea Magistrale in Scienze del Testo per le Professioni Digitali (LM-43), Università di Catania, 2021.
    • Tesi: A Large Visual Question Answering Dataset for Italian Cultural Heritage.
    • Votazione: 110/110 cum laude.
  • Laurea Triennale in Lingue e culture europee, euroamericane ed orientali (L-11), 2019.
    • Tesi: Il mito di Prometeo tra tecnica e cultura: Leopardi, Shelley, Goethe.
    • Votazione: 103/110.

Esperienze lavorative

  • 16/03/2022 - 29/10/2022, Assegnista di Ricerca, Istituto di Scienze e Tecnologie della Cognizione - Consiglio Nazionale delle Ricerche (ISTC-CNR), Roma. 
    • Programma di Ricerca: Machine-reading for knowledge engineering: studio, progettazione e sviluppo di metodi e teorie per la creazione di grafi della conoscenza a partire da corpora testuali attraverso il paradigma machine-reading.
  • 08/04/2021 - 08/10/2021, Contratto di Ricerca, Istituto di Scienze e Tecnologie della Cognizione - Consiglio Nazionale delle Ricerche (ISTC-CNR), Catania.

I miei principali interessi riguardano il Natural Language Processing (NLP) e il Machine Learning, con un focus specifico in ambito di human-centered AI. Inoltre, il mio lavoro esplora l'integrazione tra NLP e Semantic Web, approfondendo l'uso dei Knowledge Graphs e il loro rapporto con i modelli di machine learning per migliorare la rappresentazione e la gestione della conoscenza.

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.