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Sentence Simplification with Memory-Augmented Neural Networks
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
Sentence simplification aims to simplify the content and structure of complex sentences, and thus make them easier to interpret for human readers, and easier to process for downstream NLP applications. Recent advances in neural machine translation have paved the way for novel approaches to the task. In this paper, we adapt an architecture with augmented memory capacities called Neural Semantic Encoders (Munkhdalai and Yu, 2017) for sentence simplification. Our experiments demonstrate the
doi:10.18653/v1/n18-2013
dblp:conf/naacl/VuHMY18
fatcat:u6hq3ygstbdmbeab3awsnrbn7y