Adrien Bibal


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On Operations in Automatic Text Simplification
Rémi Cardon | Adrien Bibal
Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability

This paper explores the literature of automatic text simplification (ATS) centered on the notion of operations. Operations are the processed of applying certain modifications to a given text in order to transform it. In ATS, the intent of the transformation is to simplify the text. This paper overviews and structures the domain by showing how operations are defined and how they are exploited. We extensively discuss the most recent works on this notion and perform preliminary experiments to automatize operations recognition with large language models (LLMs). Through our overview of the literature and the preliminary experiment with LLMs, this paper provides insights on the topic that can help lead to new directions in ATS research.

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Annotation Linguistique pour l’Évaluation de la Simplification Automatique de Textes
Rémi Cardon | Adrien Bibal | Rodrigo Wilkens | David Alfter | Magali Norré | Adeline Müller | Patrick Watrin | Thomas François
Actes de CORIA-TALN 2023. Actes de la 30e Conférence sur le Traitement Automatique des Langues Naturelles (TALN), volume 4 : articles déjà soumis ou acceptés en conférence internationale

L’évaluation des systèmes de simplification automatique de textes (SAT) est une tâche difficile, accomplie à l’aide de métriques automatiques et du jugement humain. Cependant, d’un point de vue linguistique, savoir ce qui est concrètement évalué n’est pas clair. Nous proposons d’annoter un des corpus de référence pour la SAT, ASSET, que nous utilisons pour éclaircir cette question. En plus de la contribution que constitue la ressource annotée, nous montrons comment elle peut être utilisée pour analyser le comportement de SARI, la mesure d’évaluation la plus populaire en SAT. Nous présentons nos conclusions comme une étape pour améliorer les protocoles d’évaluation en SAT à l’avenir.


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CENTAL at TSAR-2022 Shared Task: How Does Context Impact BERT-Generated Substitutions for Lexical Simplification?
Rodrigo Wilkens | David Alfter | Rémi Cardon | Isabelle Gribomont | Adrien Bibal | Watrin Patrick | Marie-Catherine De marneffe | Thomas François
Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)

Lexical simplification is the task of substituting a difficult word with a simpler equivalent for a target audience. This is currently commonly done by modeling lexical complexity on a continuous scale to identify simpler alternatives to difficult words. In the TSAR shared task, the organizers call for systems capable of generating substitutions in a zero-shot-task context, for English, Spanish and Portuguese. In this paper, we present the solution we (the cental team) proposed for the task. We explore the ability of BERT-like models to generate substitution words by masking the difficult word. To do so, we investigate various context enhancement strategies, that we combined into an ensemble method. We also explore different substitution ranking methods. We report on a post-submission analysis of the results and present our insights for potential improvements. The code for all our experiments is available at

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Is Attention Explanation? An Introduction to the Debate
Adrien Bibal | Rémi Cardon | David Alfter | Rodrigo Wilkens | Xiaoou Wang | Thomas François | Patrick Watrin
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

The performance of deep learning models in NLP and other fields of machine learning has led to a rise in their popularity, and so the need for explanations of these models becomes paramount. Attention has been seen as a solution to increase performance, while providing some explanations. However, a debate has started to cast doubt on the explanatory power of attention in neural networks. Although the debate has created a vast literature thanks to contributions from various areas, the lack of communication is becoming more and more tangible. In this paper, we provide a clear overview of the insights on the debate by critically confronting works from these different areas. This holistic vision can be of great interest for future works in all the communities concerned by this debate. We sum up the main challenges spotted in these areas, and we conclude by discussing the most promising future avenues on attention as an explanation.

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L’Attention est-elle de l’Explication ? Une Introduction au Débat (Is Attention Explanation ? An Introduction to the Debate )
Adrien Bibal | Remi Cardon | David Alfter | Rodrigo Wilkens | Xiaoou Wang | Thomas François | Patrick Watrin
Actes de la 29e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale

Nous présentons un résumé en français et un résumé en anglais de l’article Is Attention Explanation ? An Introduction to the Debate (Bibal et al., 2022), publié dans les actes de la conférence 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022).

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Linguistic Corpus Annotation for Automatic Text Simplification Evaluation
Rémi Cardon | Adrien Bibal | Rodrigo Wilkens | David Alfter | Magali Norré | Adeline Müller | Watrin Patrick | Thomas François
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Evaluating automatic text simplification (ATS) systems is a difficult task that is either performed by automatic metrics or user-based evaluations. However, from a linguistic point-of-view, it is not always clear on what bases these evaluations operate. In this paper, we propose annotations of the ASSET corpus that can be used to shed more light on ATS evaluation. In addition to contributing with this resource, we show how it can be used to analyze SARI’s behavior and to re-evaluate existing ATS systems. We present our insights as a step to improve ATS evaluation protocols in the future.