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Statistical and Spatio-temporal Hand Gesture Features for Sign Language Recognition using the Leap Motion Sensor ...
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Giant Pigeon and Small Person: Prompting Visually Grounded Models about the Size of Objects ...
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Zhang, Yi. - : Purdue University Graduate School, 2022
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Giant Pigeon and Small Person: Prompting Visually Grounded Models about the Size of Objects ...
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Zhang, Yi. - : Purdue University Graduate School, 2022
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pNLP-Mixer: an Efficient all-MLP Architecture for Language ...
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Multilingual Abusiveness Identification on Code-Mixed Social Media Text ...
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hate-alert@DravidianLangTech-ACL2022: Ensembling Multi-Modalities for Tamil TrollMeme Classification ...
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StableMoE: Stable Routing Strategy for Mixture of Experts ...
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BERTuit: Understanding Spanish language in Twitter through a native transformer ...
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EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification ...
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Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning ...
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Abstract:
Achieving universal translation between all human language pairs is the holy-grail of machine translation (MT) research. While recent progress in massively multilingual MT is one step closer to reaching this goal, it is becoming evident that extending a multilingual MT system simply by training on more parallel data is unscalable, since the availability of labeled data for low-resource and non-English-centric language pairs is forbiddingly limited. To this end, we present a pragmatic approach towards building a multilingual MT model that covers hundreds of languages, using a mixture of supervised and self-supervised objectives, depending on the data availability for different language pairs. We demonstrate that the synergy between these two training paradigms enables the model to produce high-quality translations in the zero-resource setting, even surpassing supervised translation quality for low- and mid-resource languages. We conduct a wide array of experiments to understand the effect of the degree of ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.2201.03110 https://arxiv.org/abs/2201.03110
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Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages ...
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Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised? ...
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Assessment of Massively Multilingual Sentiment Classifiers ...
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MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages ...
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DAMO-NLP at SemEval-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition ...
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