WenLi Zhuang

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2017

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Neobility at SemEval-2017 Task 1: An Attention-based Sentence Similarity Model
WenLi Zhuang | Ernie Chang
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper describes a neural-network model which performed competitively (top 6) at the SemEval 2017 cross-lingual Semantic Textual Similarity (STS) task. Our system employs an attention-based recurrent neural network model that optimizes the sentence similarity. In this paper, we describe our participation in the multilingual STS task which measures similarity across English, Spanish, and Arabic.
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