Lexical Simplification with the Deep Structured Similarity Model

IJCNLP 2017 · Lis Pereira, Xiaodong Liu, John Lee ·

We explore the application of a Deep Structured Similarity Model (DSSM) to ranking in lexical simplification. Our results show that the DSSM can effectively capture fine-grained features to perform semantic matching when ranking substitution candidates, outperforming the state-of-the-art on two standard datasets used for the task.

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Image Captioning

Learning Word Embeddings

Lexical Simplification

Machine Translation

Question Answering

Word Embeddings

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