Speeding up Context-based Sentence Representation Learning with Non-autoregressive Convolutional Decoding

WS 2018 Shuai TangHailin JinChen FangZhaowen WangVirginia R. de Sa

Context plays an important role in human language understanding, thus it may also be useful for machines learning vector representations of language. In this paper, we explore an asymmetric encoder-decoder structure for unsupervised context-based sentence representation learning... (read more)

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