Expertises

  • Computer Science

    • Linguistics
    • Evaluation
    • Sentiment Analysis
    • Rhetoric
    • User
  • Arts and Humanities

    • Liberty
    • System
  • Psychology

    • Narrative

Organisaties

Publicaties

2025

Using Design Thinking for Explainable AI: A Case Study Predicting the Start of the Palliative Phase in Patients with COPD or Heart Failure (2025)In Proceedings of the Second Workshop on Explainable Artificial Intelligence for the Medical Domain (EXPLIMED 2025) (CEUR workshop proceedings; Vol. 4059). Heerlien, I., Linssen, J., Gatti, L., Sappelli, M., van Gaal, B., Evering, R. & Letwory, N.

2024

A Novel Lexicon for the Moral Foundation of Liberty (2024)[Working paper › Preprint]. ArXiv.org. Araque, O., Gatti, L., Consoli, S. & Kalimeri, K.https://doi.org/10.48550/arXiv.2407.11862Investigating the Impact of Code Generation Tools (ChatGPT & Github CoPilot) on Programming Education (2024)In Proceedings of the 16th International Conference on Computer Supported Education, CSEDU 2024 (pp. 221-229) (International Conference on Computer Supported Education, CSEDU - Proceedings; Vol. 2). Science and Technology Publications, Lda. Nizamudeen, F., Gatti, L., Bouali, N. & Ahmed, F.https://doi.org/10.5220/0012628000003693Part-of-Speech Tagging for Northern Kurdish (2024)In Joint Workshop on Multiword Expressions and Universal Dependencies, MWE-UD 2024 at LREC-COLING 2024 - Workshop Proceedings (pp. 70-80). European Language Resources Association (ELRA). Morad, P., Ahmadi, S. & Gatti, L.https://aclanthology.org/2024.mwe-1.11

2023

What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - code (2023)[Dataset Types › Dataset]. 4TU.Centre for Research Data. Liscio, E., Araque, O., Gatti, L., Constantinescu, I., Jonker, C. M., Kalimeri, K. & Murukannaiah, P. K.https://doi.org/10.4121/1e71138c-be26-4652-971a-48a84837df8eWhat does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - models (2023)[Dataset Types › Dataset]. 4TU.Centre for Research Data. Liscio, E., Araque, O., Gatti, L., Constantinescu, I., Jonker, C. M., Kalimeri, K. & Murukannaiah, P. K.https://doi.org/10.4121/646b20e3-e24f-452d-938a-bcb6ce30913cWhat does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - supplemental material (2023)[Dataset Types › Dataset]. 4TU.Centre for Research Data. Liscio, E., Araque, O., Gatti, L., Constantinescu, I., Jonker, C. M., Kalimeri, K. & Murukannaiah, P. K.https://doi.org/10.4121/cd43b76a-850e-4222-ab81-5a20b7b1b93dBeyond the Headlines: Understanding Sentiments and Morals Impacting Female Employment in Spain (2023)[Contribution to conference › Paper] Workshop on Data for the Wellbeing of the Most Vulnerable, DWMV 2023. Araque, O., Barbaglia, L., Berlingieri, F., Colagrossi, M., Gatti, L., Consoli, S., Mauri, C. & Kalimeri, K.https://workshop-proceedings.icwsm.org/abstract.php?id=2023_03Tomea: an Explainable Method for Comparing Morality Classifiers across Domains (2023)[Contribution to conference › Abstract] Joint International Scientific Conferences on AI and Machine Learning, BNAIC/BeNeLearn 2023. Liscio, E., Araque, O., Gatti, L., Constantinescu, I., Jonker, C. M., Kalimeri, K. & Murukannaiah, P. K.https://bnaic2023.tudelft.nl/static/media/BNAICBENELEARN_2023_paper_29.6e3e33970df5a3d9592a.pdfWhat does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric (2023)In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 14113-14132) (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1). Association for Computational Linguistics (ACL). Liscio, E., Araque, O., Gatti, L., Constantinescu, I., Jonker, C. M., Kalimeri, K. & Murukannaiah, P. K.https://aclanthology.org/2023.acl-long.789

Onderzoeksprofielen

Lopende projecten

Producing Affective Language

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