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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 14 of 14 1 Rethinking Automatic Evaluation in Sentence Simplification Scialom, Thomas; Martin, Louis; Staiano, Jacopo; de la Clergerie, Éric Villemonte; Sagot, Benoît In: https://hal.inria.fr/hal-03199901 ; 2021 (2021) Abstract: Automatic evaluation remains an open research question in Natural Language Generation. In the context of Sentence Simplification, this is particularly challenging: the task requires by nature to replace complex words with simpler ones that shares the same meaning. This limits the effectiveness of n-gram based metrics like BLEU. Going hand in hand with the recent advances in NLG, new metrics have been proposed, such as BERTScore for Machine Translation. In summarization, the QuestEval metric proposes to automatically compare two texts by questioning them. In this paper, we first propose a simple modification of QuestEval allowing it to tackle Sentence Simplification. We then extensively evaluate the correlations w.r.t. human judgement for several metrics including the recent BERTScore and QuestEval, and show that the latter obtain state-of-the-art correlations, outperforming standard metrics like BLEU and SARI. More importantly, we also show that a large part of the correlations are actually spurious for all the metrics. To investigate this phenomenon further, we release a new corpus of evaluated simplifications, this time not generated by systems but instead, written by humans. This allows us to remove the spurious correlations and draw very different conclusions from the original ones, resulting in a better understanding of these metrics. In particular, we raise concerns about very low correlations for most of traditional metrics. Our results show that the only significant measure of the Meaning Preservation is our adaptation of QuestEval. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] URL: https://hal.inria.fr/hal-03199901 BASE Hide details 2 Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering Riabi, Arij; Scialom, Thomas; Keraron, Rachel... In: https://hal.inria.fr/hal-03109187 ; 2021 (2021) BASE Show details 3 QuestEval: Summarization Asks for Fact-based Evaluation Scialom, Thomas; Dray, Paul-Alexis; Gallinari, Patrick... In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ; https://hal.sorbonne-universite.fr/hal-03541895 ; Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Nov 2021, Punta Cana (en ligne), Dominican Republic. pp.6594-6604, ⟨10.18653/v1/2021.emnlp-main.529⟩ ; https://2021.emnlp.org/ (2021) BASE Show details 4 MLSUM: The Multilingual Summarization Corpus Scialom, Thomas; Dray, Paul-Alexis; Lamprier, Sylvain... In: https://hal.sorbonne-universite.fr/hal-02989017 ; 2020 (2020) BASE Show details 5 MLSUM: The Multilingual Summarization Corpus Scialom, Thomas; Dray, Paul-Alexis; Lamprier, Sylvain... In: 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ; https://hal.sorbonne-universite.fr/hal-03364407 ; 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov 2020, Online, France. pp.8051-8067, ⟨10.18653/v1/2020.emnlp-main.647⟩ (2020) BASE Show details 6 MLSUM: The Multilingual Summarization Corpus ... Scialom, Thomas; Dray, Paul-Alexis; Lamprier, Sylvain. - : arXiv, 2020 BASE Show details 7 Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering ... Riabi, Arij; Scialom, Thomas; Keraron, Rachel. - : arXiv, 2020 BASE Show details 8 Answers Unite! Unsupervised Metrics for Reinforced Summarization Models Scialom, Thomas; Lamprier, Sylvain; Piwowarski, Benjamin... In: 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) ; https://hal.sorbonne-universite.fr/hal-02350999 ; 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Nov 2019, Hong Kong, China. pp.3237-3247, ⟨10.18653/v1/D19-1320⟩ (2019) BASE Show details 9 Self-Attention Architectures for Answer-Agnostic Neural Question Generation Scialom, Thomas; Piwowarski, Benjamin; Staiano, Jacopo In: ACL 2019 - Annual Meeting of the Association for Computational Linguistics ; https://hal.sorbonne-universite.fr/hal-02350993 ; ACL 2019 - Annual Meeting of the Association for Computational Linguistics, Jul 2019, Florence, Italy. pp.6027-6032, ⟨10.18653/v1/P19-1604⟩ (2019) BASE Show details 10 Answers Unite! Unsupervised Metrics for Reinforced Summarization Models ... Scialom, Thomas; Lamprier, Sylvain; Piwowarski, Benjamin. - : arXiv, 2019 BASE Show details 11 DepecheMood++: a Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques ... Araque, Oscar; Gatti, Lorenzo; Staiano, Jacopo. - : arXiv, 2018 BASE Show details 12 Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines ... Mansar, Youness; Gatti, Lorenzo; Ferradans, Sira. - : arXiv, 2017 BASE Show details 13 Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and Virality ... Guerini, Marco; Staiano, Jacopo. - : arXiv, 2015 BASE Show details 14 DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News ... Staiano, Jacopo; Guerini, Marco. - : arXiv, 2014 BASE Show details

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