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1
AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization ...
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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)
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3
Multitask Easy-First Dependency Parsing ...
Abstract: In this paper we present a parsing model for projective dependency trees which takes advantage of the existence of complementary dependency annotations which is the case in Arabic, with the availability of CATiB and UD treebanks. Our system performs syntactic parsing according to both annotation types jointly as a sequence of arc-creating operations, and partially created trees for one annotation are also available to the other as features for the score function. This method gives error reduction of 9.9% on CATiB and 6.1% on UD compared to a strong baseline, and ablation tests show that the main contribution of this reduction is given by sharing tree representation between tasks, and not simply sharing BiLSTM layers as is often performed in NLP multitask systems. ...
Keyword: Computer and Information Science; Natural Language Processing; Neural Network
URL: https://dx.doi.org/10.48448/bh61-zb18
https://underline.io/lecture/6319-multitask-easy-first-dependency-parsing
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4
Proceedings of the Fifth Arabic Natural Language Processing Workshop
Bouamor, Houda; Zaghouani, Wajdi. - : Association for Computational Linguistics, 2020
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5
AraWEAT: Multidimensional analysis of biases in Arabic word embeddings
Lauscher, Anne; Takieddin, Rafik; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2020
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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)
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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)
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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)
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9
Maximum-entropy word alignment and posterior-based phrase extraction for machine translation
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 28 (2014) 1, 19-56
OLC Linguistik
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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)
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11
Discriminative Alignment Models For Statistical Machine Translation ; Modèles Discriminants d'Alignement Pour La Traduction Automatique Statistique
Tomeh, Nadi. - : HAL CCSD, 2012
In: https://tel.archives-ouvertes.fr/tel-00720250 ; Other [cs.OH]. Université Paris Sud - Paris XI, 2012. English. ⟨NNT : 2012PA112104⟩ (2012)
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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)
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