Michele Linardi
Publications
Publications
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Machine Learning is heading to the SUD (Socially Unacceptable Discourse) analysis: From Shallow Learning to Large Language Models to the rescue, where do we stand?Louis Cotgrove; Laura Herzberg; Harald Lüngen. Exploring digitally-mediated communication with corpora, De Gruyter, pp.225-256, 2025, 9783111432595. ⟨10.1515/9783111434018-011⟩ |
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[MASK]ED -Language Modeling for Explainable Classification and Disentangling of Socially Unacceptable DiscourseFindings of the Association for Computational Linguistics: EMNLP 2025, Nov 2025, Suzhou, France. pp.14870-14883, ⟨10.18653/v1/2025.findings-emnlp.803⟩ |
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Analysis of Socially Unacceptable Discourse with Zero-shot LearningInternational Conference on CMC and Social Media Corpora for the Humanities, University Côte d’Azur, France, 2024, Sep 2024, Nice (FRANCE), France |
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Studying Socially Unacceptable Discourse Classification (SUD) through different eyes: "Are we on the same page ?International Conference on CMC and Social Media Corpora for the Humanities, Sep 2023, Mannheim, Germany, Germany |
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Evaluating Explanation Methods of Multivariate Time Series Classification through Causal LensesIEEE International Conference on Data Science and Advanced Analytics (DSAA), Oct 2023, Tessalonique, Grèce, Greece |
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Unsupervised Time Series Anomaly Detection: The Road to Effective ExplainabilityConférence francophone sur l'Extraction et la Gestion des Connaissances 24-28 janvier 2022 (Atelier EXPLAIN'AI ), Jan 2022, Blois, France, France |
ChaseFUN: a Data Exchange Engine for Functional Dependencies at ScaleInternational Conference on Extending DatabaseTechnology (EDBT), Mar 2017, Venice, Italy. pp.534--537 |
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Functional Dependencies Unleashed for Scalable Data ExchangeInternational Conference on Scientific and Statistical Database Management (SSDBM), Jul 2016, Budapest, Hungary. pp.2:1-2:12, ⟨10.1145/2949689.2949698⟩ |
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Towards a new Contextualized Annotation Schema for Unacceptable and Extreme Speech (CUES) to Unleash Generalization Capability of ML modelsStudii de lingvistică, 2024, 14 (2), pp.63-94 |
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Variable-length similarity search for very large data series : subsequence matching, motif and discord detectionDatabases [cs.DB]. Université Sorbonne Paris Cité, 2019. English. ⟨NNT : 2019USPCB056⟩ |