Irene Dini


2023

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Coherent or Not? Stressing a Neural Language Model for Discourse Coherence in Multiple Languages
Dominique Brunato | Felice Dell’Orletta | Irene Dini | Andrea Amelio Ravelli
Findings of the Association for Computational Linguistics: ACL 2023

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.

2022

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How about Time? Probing a Multilingual Language Model for Temporal Relations
Tommaso Caselli | Irene Dini | Felice Dell’Orletta
Proceedings of the 29th International Conference on Computational Linguistics

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 detrimen- tal 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.