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Data Augmentation for Spoken Language Understanding via Joint Variational Generation
Data scarcity is one of the main obstacles of domain adaptation in spoken language understanding (SLU) due to the high cost of creating manually tagged SLU datasets.
Improving Visually Grounded Sentence Representations with Self-Attention
Sentence representation models trained only on language could potentially suffer from the grounding problem.
Supersense Tagging with a Combination of Character, Subword, and Word-level Representations
Recently, there has been increased interest in utilizing characters or subwords for natural language processing (NLP) tasks.
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