[{"id":366732,"last_updated":"2024-01-10 11:02:52","id_people":491078,"institutes":["ILC"],"type":"conference_article","type_order":5,"type_people":"conferenceObject","title":"Coherent or Not? Stressing a Neural Language Model for Discourse Coherence in Multiple Languages","year":2023,"authors_people":"Dominique Brunato; Felice Dell'Orletta; Irene Dini; Andrea Amelio Ravelli","authors_cnr":["Ravelli, Andrea Amelio","Dini, Irene","Dell'Orletta, Felice","Brunato, Dominique Pierina"],"authors_cnr_id":["14329","21125"],"authors_cnr_institute":[""],"authors":["Brunato, D.","Dell'Orletta, F.","Dini, I.","Ravelli, A. A."],"abstract":"In this study, we investigate the capability of a Neural Language Model (NLM) to distinguish between coherent and incoherent text, where the latter has been artificially created to gradually undermine local coherence within text. While previous research on coherence assessment using NLMs has primarily focused on English, we extend our investigation to multiple languages. We employ a consistent evaluation framework to compare the performance of monolingual and multilingual models in both in-domain and out-domain settings. Additionally, we explore the model's performance in a cross-language scenario.","keywords":["text coherence","neural language models","multilingual corpora"],"pages":"10690-10700","url":"https:\/\/aclanthology.org\/2023.findings-acl.680","volume":"","doi":"10.18653\/v1\/2023.findings-acl.680","editors_people":"","editors":[""],"published":"","publisher":"Association for Computational Linguistics (Stroudsburg, USA)","issn":"","isbn":"978-1-959429-62-3","conference_name":"61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)","conference_place":"Toronto, Canada","conference_date":"9-14\/07\/2023"},{"id":343041,"last_updated":"2023-11-06 19:31:12","id_people":472144,"institutes":["ILC"],"type":"conference_article","type_order":5,"type_people":"conferenceObject","title":"How About Time? Probing a Multilingual Language Model for Temporal Relations","year":2022,"authors_people":"Caselli T., Dini I., Dell'Orletta F.","authors_cnr":["Dini, Irene","Dell'Orletta, Felice"],"authors_cnr_id":["14329"],"authors_cnr_institute":[""],"authors":["Caselli, T.","Dini, I.","Dell'Orletta, F."],"abstract":"This paper presents a comprehensive set of probing experiments using a multilingual language model, XLM-R, for temporal relation classification between events in four languages. Results show an advantage of contextualized embeddings over static ones and a detrimental role of sentence level embeddings. While obtaining competitive results against state-of-the-art systems, our probes indicate a lack of suitable encoded information to properly address this task.","keywords":["Natural Language Processing","Neural Language Models","Temporal Relation Classification"],"pages":"","url":"https:\/\/aclanthology.org\/2022.coling-1.283\/","volume":"","doi":"","editors_people":"","editors":[""],"published":"Proceedings of the 29th International Conference on Computational Linguistics, COLING 2022","publisher":"","issn":"","isbn":"","conference_name":"International Conference on Computational Linguistics (COLING)","conference_place":"Gyeongju, Republic of Kore","conference_date":"12-17 ottobre 2022"}]