1 |
AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization ...
|
|
|
|
Abstract:
Like most natural language understanding and generation tasks, state-of-the-art models for summarization are transformer-based sequence-to-sequence architectures that are pretrained on large corpora. While most existing models focused on English, Arabic remained understudied. In this paper we propose AraBART, the first Arabic model in which the encoder and the decoder are pretrained end-to-end, based on BART. We show that AraBART achieves the best performance on multiple abstractive summarization datasets, outperforming strong baselines including a pretrained Arabic BERT-based model and multilingual mBART and mT5 models. ...
|
|
Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
|
|
URL: https://arxiv.org/abs/2203.10945 https://dx.doi.org/10.48550/arxiv.2203.10945
|
|
BASE
|
|
Hide details
|
|
2 |
Multitask Easy-First Dependency Parsing: Exploiting Complementarities of Different Dependency Representations
|
|
|
|
In: Proceedings of the 28th International Conference on Computational Linguistics ; 28th International Conference on Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03168039 ; 28th International Conference on Computational Linguistics, Dec 2020, Barcelona (on line), Spain. ⟨10.18653/v1/2020.coling-main.225⟩ (2020)
|
|
BASE
|
|
Show details
|
|
4 |
Proceedings of the Fifth Arabic Natural Language Processing Workshop
|
|
|
|
BASE
|
|
Show details
|
|
5 |
AraWEAT: Multidimensional analysis of biases in Arabic word embeddings
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Deep Lexical Segmentation and Syntactic Parsing in the Easy-First Dependency Framework
|
|
|
|
In: NAACL ; https://hal.archives-ouvertes.fr/hal-01494125 ; NAACL, 2016, San Diego, United States (2016)
|
|
BASE
|
|
Show details
|
|
7 |
Pattern mining and CRF for symptoms recognition in biomedical texts ; Fouille de motifs et CRF pour la reconnaissance de symptômes dans les textes biomédicaux
|
|
|
|
In: 23e conférence sur le Traitement Automatique des Langues Naturelles (TALN’16) ; https://halshs.archives-ouvertes.fr/halshs-01727081 ; 23e conférence sur le Traitement Automatique des Langues Naturelles (TALN’16), Jul 2016, Paris, France. pp.194-206 (2016)
|
|
BASE
|
|
Show details
|
|
8 |
Weakly-supervised Symptom Recognition for Rare Diseases in Biomedical Text
|
|
|
|
In: 15th International Symposium on Intelligent Data Analysis ; https://halshs.archives-ouvertes.fr/halshs-01727071 ; 15th International Symposium on Intelligent Data Analysis, Oct 2016, Stockholm, Sweden (2016)
|
|
BASE
|
|
Show details
|
|
10 |
LIPN: Introducing a new Geographical Context Similarity Measure and a Statistical Similarity Measure based on the Bhattacharyya coefficient
|
|
|
|
In: SemEval 2014 ; https://hal.archives-ouvertes.fr/hal-01068277 ; SemEval 2014, Aug 2014, Dublin, Ireland. pp.400-405 (2014)
|
|
BASE
|
|
Show details
|
|
11 |
Discriminative Alignment Models For Statistical Machine Translation ; Modèles Discriminants d'Alignement Pour La Traduction Automatique Statistique
|
|
|
|
In: https://tel.archives-ouvertes.fr/tel-00720250 ; Other [cs.OH]. Université Paris Sud - Paris XI, 2012. English. ⟨NNT : 2012PA112104⟩ (2012)
|
|
BASE
|
|
Show details
|
|
12 |
Designing an improved discriminative word aligner
|
|
|
|
In: International Conference on Intelligent Text Processing and Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01960730 ; International Conference on Intelligent Text Processing and Computational Linguistics, Jan 2011, Tokyo, Japan (2011)
|
|
BASE
|
|
Show details
|
|
|
|