Trained models for the paper "What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric", published at ACL '23. The models were trained on the MFTC datasets with the sequential paradigm. Each of the seven models was trained on six MFTC datasets and continued training on a portion of the seventh. The code that contains instructions on how to use the models is available at this DOI: 10.4121/1e71138c-be26-4652-971a-48a84837df8e
Liscio, E., Araque, O., Gatti, L., Constantinescu, I., Jonker, C. M., Kalimeri, K. & Murukannaiah, P. K., 2023, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).2023 ed.Association for Computational Linguistics (ACL), p. 14113-1413220 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; vol. 1).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
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Liscio, E. (Creator), Araque, O. (Creator), Gatti, L. (Creator), Constantinescu, I. (Creator), Jonker, C. M. (Creator), Kalimeri, K. (Creator), Murukannaiah, P. K. (Creator) (18 Dec 2023). What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - models. 4TU.Centre for Research Data. 10.4121/646b20e3-e24f-452d-938a-bcb6ce30913c