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Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ...
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Abstract:
Semi-supervised learning through deep generative models and multi-lingual pretraining techniques have orchestrated tremendous success across different areas of NLP. Nonetheless, their development has happened in isolation, while the combination of both could potentially be effective for tackling task-specific labelled data shortage. To bridge this gap, we combine semi-supervised deep generative models and multi-lingual pretraining to form a pipeline for document classification task. Compared to strong supervised learning baselines, our semi-supervised classification framework is highly competitive and outperforms the state-of-the-art counterparts in low-resource settings across several languages. ... : EACL 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2101.10717 https://dx.doi.org/10.48550/arxiv.2101.10717
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It Is Not As Good As You Think! Evaluating Simultaneous Machine Translation on Interpretation Data ...
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A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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Self-Alignment Pretraining for Biomedical Entity Representations
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Liu, Fangyu; Shareghi, Ehsan; Meng, Zaiqiao. - : Association for Computational Linguistics, 2021. : Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
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A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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Show Some Love to Your n-grams: A Bit of Progress and Stronger n-gram Language Modeling Baselines ...
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Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees ...
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Structured Prediction of Sequences and Trees using Infinite Contexts ...
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