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1
Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
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2
On Homophony and Rényi Entropy ...
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3
On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu ...
Mehmood, Khawar. - : UNSW Sydney, 2021
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4
Generative Imagination Elevates Machine Translation ...
NAACL 2021 2021; Li, Lei; Long, Quanyu. - : Underline Science Inc., 2021
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5
Multilingual Email Zoning - Segmenting Multilingual Email Text Into Zones
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6
Contextualised sentiment analysis in the financial domain
Daudert, Tobias. - : NUI Galway, 2021
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7
Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ...
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8
Signed Coreference Resolution ...
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Backtranslation in Neural Morphological Inflection ...
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10
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.477/ Abstract: Current approaches to incorporating terminology constraints in machine translation (MT) typically assume that the constraint terms are provided in their correct morphological forms. This limits their application to real-world scenarios where constraint terms are provided as lemmas. In this paper, we introduce a modular framework for incorporating lemma constraints in neural MT (NMT) in which linguistic knowledge and diverse types of NMT models can be flexibly applied. It is based on a novel cross-lingual inflection module that inflects the target lemma constraints based on the source context. We explore linguistically motivated rule-based and data-driven neural-based inflection modules and design English-German health and English-Lithuanian news test suites to evaluate them in domain adaptation and low-resource MT settings. Results show that our rule-based inflection module helps NMT models incorporate lemma constraints more ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
URL: https://underline.io/lecture/37994-rule-based-morphological-inflection-improves-neural-terminology-translation
https://dx.doi.org/10.48448/y0cj-my74
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11
Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
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12
A Prototype Free/Open-Source Morphological Analyser and Generator for Sakha ...
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13
Automatic Error Type Annotation for Arabic ...
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14
Developing Conversational Data and Detection of Conversational Humor in Telugu ...
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15
An Information-Theoretic Characterization of Morphological Fusion ...
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16
Cross-document Event Identity via Dense Annotation ...
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17
Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning ...
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18
(Mis)alignment Between Stance Expressed in Social Media Data and Public Opinion Surveys ...
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19
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach ...
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20
Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization ...
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