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A Neural Pairwise Ranking Model for Readability Assessment ...
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SMDT: Selective Memory-Augmented Neural Document Translation ...
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CausalKG: Causal Knowledge Graph Explainability using interventional and counterfactual reasoning ...
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Learn from Structural Scope: Improving Aspect-Level Sentiment Analysis with Hybrid Graph Convolutional Networks ...
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Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese ...
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Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ...
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Modeling Intensification for Sign Language Generation: A Computational Approach ...
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A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition ...
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Open Source HamNoSys Parser for Multilingual Sign Language Encoding ...
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A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets ...
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Sign Language Video Retrieval with Free-Form Textual Queries ...
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Sign Language Recognition System using TensorFlow Object Detection API ...
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pNLP-Mixer: an Efficient all-MLP Architecture for Language ...
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ParaNames: A Massively Multilingual Entity Name Corpus ...
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Abstract:
This preprint describes work in progress on ParaNames, a multilingual parallel name resource consisting of names for approximately 14 million entities. The included names span over 400 languages, and almost all entities are mapped to standardized entity types (PER/LOC/ORG). Using Wikidata as a source, we create the largest resource of this type to-date. We describe our approach to filtering and standardizing the data to provide the best quality possible. ParaNames is useful for multilingual language processing, both in defining tasks for name translation/transliteration and as supplementary data for tasks such as named entity recognition and linking. We demonstrate an application of ParaNames by training a multilingual model for canonical name translation to and from English. Our resource is released at \url{https://github.com/bltlab/paranames} under a Creative Commons license (CC BY 4.0). ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2202.14035 https://arxiv.org/abs/2202.14035
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Listening to Affected Communities to Define Extreme Speech: Dataset and Experiments ...
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Cross-Lingual Text-to-Speech Using Multi-Task Learning and Speaker Classifier Joint Training ...
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Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation ...
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Sememe Prediction for BabelNet Synsets using Multilingual and Multimodal Information ...
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Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation ...
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