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ID: associatedtexts
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Learning Semantic Correspondences from Noisy Data-text Pairs by Local-to-Global Alignments
AbstractLearning semantic correspondences between structured input data (e.g., slot-value pairs) and associated texts is a core problem for many downstream NLP applications, e.g., data-to-text generation. Large-scale datasets recently proposed for …...