Výsledky vyhledávání - "Gadek, Guillaume"

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HYBRINFOX at CheckThat! 2024 -- Task 1: Enhancing Language Models with Structured Information for Check-Worthiness Estimation

Autor: Faye, Géraud, Casanova, Morgane, Icard, Benjamin, Chanson, Julien, Gadek, Guillaume, Gravier, Guillaume, Égré, Paul

This paper summarizes the experiments and results of the HYBRINFOX team for the CheckThat! 2024 - Task 1 competition. We propose an approach enriching Language Models such as RoBERTa with embeddings produced by triples (subject ; predicate ; object)

Externí odkaz: http://arxiv.org/abs/2407.03850

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HYBRINFOX at CheckThat! 2024 -- Task 2: Enriching BERT Models with the Expert System VAGO for Subjectivity Detection

Autor: Casanova, Morgane, Chanson, Julien, Icard, Benjamin, Faye, Géraud, Gadek, Guillaume, Gravier, Guillaume, Égré, Paul

This paper presents the HYBRINFOX method used to solve Task 2 of Subjectivity detection of the CLEF 2024 CheckThat! competition. The specificity of the method is to use a hybrid system, combining a RoBERTa model, fine-tuned for subjectivity detection

Externí odkaz: http://arxiv.org/abs/2407.03770

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A Multi-Label Dataset of French Fake News: Human and Machine Insights

Autor: Icard, Benjamin, Maine, François, Casanova, Morgane, Faye, Géraud, Chanson, Julien, Gadek, Guillaume, Atemezing, Ghislain, Bancilhon, François, Égré, Paul

We present a corpus of 100 documents, OBSINFOX, selected from 17 sources of French press considered unreliable by expert agencies, annotated using 11 labels by 8 annotators. By collecting more labels than usual, by more annotators than is typically d

Externí odkaz: http://arxiv.org/abs/2403.16099

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Exposing propaganda: an analysis of stylistic cues comparing human annotations and machine classification

Autor: Faye, Géraud, Icard, Benjamin, Casanova, Morgane, Chanson, Julien, Maine, François, Bancilhon, François, Gadek, Guillaume, Gravier, Guillaume, Égré, Paul

This paper investigates the language of propaganda and its stylistic features. It presents the PPN dataset, standing for Propagandist Pseudo-News, a multisource, multilingual, multimodal dataset composed of news articles extracted from websites ident

Externí odkaz: http://arxiv.org/abs/2402.03780

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Combining Vagueness Detection with Deep Learning to Identify Fake News

Autor: Guélorget, Paul, Icard, Benjamin, Gadek, Guillaume, Gahbiche, Souhir, Gatepaille, Sylvain, Atemezing, Ghislain, Égré, Paul

In this paper, we combine two independent detection methods for identifying fake news: the algorithm VAGO uses semantic rules combined with NLP techniques to measure vagueness and subjectivity in texts, while the classifier FAKE-CLF relies on Convolu

Externí odkaz: http://arxiv.org/abs/2110.14780

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