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Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)
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In: ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora ; https://hal.archives-ouvertes.fr/hal-03623351 ; ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora, Jun 2022, Marseille, France ; https://www.clarin.eu/ParlaCLARIN-III (2022)
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Ensemble of Opinion Dynamics Models to Understand the Role of the Undecided in the Vaccination Debate ...
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Zum Ungleichgewicht digital vermittelten Sachunterrichts und sprachlich-kommunikativer Anforderungen ...
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Zum Ungleichgewicht digital vermittelten Sachunterrichts und sprachlich-kommunikativer Anforderungen
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In: Sachunterricht in der Informationsgesellschaft. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 114-121. - (Probleme und Perspektiven des Sachunterrichts; 32) (2022)
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Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive Approach Using Transformers ...
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MMTAfrica: Multilingual Machine Translation for African Languages ...
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A New Generation of Perspective API: Efficient Multilingual Character-level Transformers ...
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MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset ...
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Korean Online Hate Speech Dataset for Multilabel Classification: How Can Social Science Improve Dataset on Hate Speech? ...
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Quantifying knowledge synchronisation in the 21st century ...
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An NLP Solution to Foster the Use of Information in Electronic Health Records for Efficiency in Decision-Making in Hospital Care ...
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Networks and Identity Drive Geographic Properties of the Diffusion of Linguistic Innovation ...
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Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study ...
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Abstract:
In this work, we present an extensive study on the use of pre-trained language models for the task of automatic Counter Narrative (CN) generation to fight online hate speech in English. We first present a comparative study to determine whether there is a particular Language Model (or class of LMs) and a particular decoding mechanism that are the most appropriate to generate CNs. Findings show that autoregressive models combined with stochastic decodings are the most promising. We then investigate how an LM performs in generating a CN with regard to an unseen target of hate. We find out that a key element for successful `out of target' experiments is not an overall similarity with the training data but the presence of a specific subset of training data, i.e. a target that shares some commonalities with the test target that can be defined a-priori. We finally introduce the idea of a pipeline based on the addition of an automatic post-editing step to refine generated CNs. ... : To appear in "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL): Findings" ...
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Keyword:
Computation and Language cs.CL; Computers and Society cs.CY; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2204.01440 https://arxiv.org/abs/2204.01440
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Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations ...
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Towards Responsible Natural Language Annotation for the Varieties of Arabic ...
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Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models ...
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Who will share Fake-News on Twitter? Psycholinguistic cues in online post histories discriminate Between actors in the misinformation ecosystem ...
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