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One model for the learning of language.
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In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022)
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Computational Measures of Deceptive Language: Prospects and Issues
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In: ISSN: 2297-900X ; EISSN: 2297-900X ; Frontiers in Communication ; https://hal.archives-ouvertes.fr/hal-03629780 ; Frontiers in Communication, Frontiers, 2022, 7, pp.792378. ⟨10.3389/fcomm.2022.792378⟩ (2022)
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Animal linguistics in the making: the Urgency Principle and titi monkeys’ alarm system
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In: ISSN: 0394-9370 ; Ethology Ecology and Evolution ; https://hal.inrae.fr/hal-03518874 ; Ethology Ecology and Evolution, Taylor & Francis, 2022, pp.1-17. ⟨10.1080/03949370.2021.2015452⟩ (2022)
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A Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
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In: Journal of Open Humanities Data; Vol 8 (2022); 3 ; 2059-481X (2022)
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Using Machine Learning for Pharmacovigilance: A Systematic Review
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In: Pharmaceutics; Volume 14; Issue 2; Pages: 266 (2022)
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Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
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Hebrew Transformed: Machine Translation of Hebrew Using the Transformer Architecture
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Abstract:
This thesis presents the first known end-to-end application to Hebrew language of Google’s state-of-the-art Transformer architecture for natural language processing (NLP). The state of the art in machine translation (MT) of Hebrew remains poor. Scholarly work in MT, deep learning (DL), and other areas of NLP for Hebrew began to develop much later and remains much less mature than for other languages. The problem is difficult because of the nature of Hebrew as a morphologically-rich language (MRL), the small size of the total corpus of electronic Hebrew documents available as training material, and the small size of the Hebrew-literate computing community worldwide. Nonetheless, significant advances in Hebrew NLP tools, data, methods, and scholarly infrastructure over the last 15 years, combined with recent advances in general NLP and MT over the last few years, especially the rise of neural networks and deep learning, create an enticing opportunity to attempt to advance the current state of Hebrew MT. More specifically, Google’s Transformer neural network and associated technologies such as bidirectional encoder representations from Transformers (BERT) have revolutionized general MT and hold great promise for improving automatic Hebrew translation. This thesis demonstrates that, as measured by METEOR scores, a basic Hebrew Transformer trained in a few hours on a single GPU (graphics processing unit) exceeds the current performance of Google Translate on in-genre Hebrew translation tasks and is not far behind Google Translate on Hebrew translation tasks in general.
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Keyword:
Artificial intelligence; bidirectional encoder representations from transformers (BERT); computational linguistics; Computer science; hebrew; Linguistics; machine translation; natural language processing (NLP); transformer
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URL: https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37370749
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| 12 |
Causal and Semantic Relations in L2 Text Processing: An Eye-Tracking Study
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Nahatame, Shingo. - : University of Hawaii National Foreign Language Resource Center, 2022. : Center for Language & Technology, 2022
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| 13 |
Phylogenetic trees: Grammar versus vocabulary
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In: Russian Journal of Linguistics, Vol 26, Iss 1, Pp 31-50 (2022) (2022)
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| 14 |
French de and en as expressions of the genitive case: a unified analysis within LFG and computational implementation in XLE1
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In: DELTA: Documentação e Estudos em Linguística Teórica e Aplicada; v. 37 n. 1 (2021) ; 1678-460X ; 0102-4450 (2022)
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| 15 |
Universals of Linguistic Idiosyncrasy in Multilingual Computational Linguistics ; Universals of Linguistic Idiosyncrasy in Multilingual Computational Linguistics: Dagstuhl Seminar 21351
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In: Universals of Linguistic Idiosyncrasy in Multilingual Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03507948 ; Universals of Linguistic Idiosyncrasy in Multilingual Computational Linguistics, Aug 2021, pp.89--138, 2021, 2192-5283. ⟨10.4230/DagRep.11.7.89⟩ ; https://gitlab.com/unlid/dagstuhl-seminar/-/wikis/home (2021)
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Type-logical investigations: proof-theoretic, computational and linguistic aspects of modern type-logical grammars
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In: https://hal-lirmm.ccsd.cnrs.fr/tel-03452731 ; Computation and Language [cs.CL]. Université Montpellier, 2021 (2021)
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Arc-Eager Construction Provides Learning Advantage Beyond Stack Management
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Dialogue Modeling in a Dynamic Framework ; Modélisation dynamique des dialogues
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In: https://hal.archives-ouvertes.fr/tel-03541628 ; Computation and Language [cs.CL]. Université de Lorraine; École doctorale IAEM Lorraine - Informatique, Automatique, Électronique - Électrotechnique, Mathématiques de Lorraine, 2021. English. ⟨NNT : 2021LORR0199⟩ (2021)
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| 19 |
SM to: Is there a bilingual disadvantage for word segmentation? A computational modeling approach ...
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| 20 |
Micropoetry meets Neurocognitive Poetics ... : Influence of Associations on the Reception of Poetry ...
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