@inproceedings{zhuang-chang-2017-neobility,
title = "Neobility at {S}em{E}val-2017 Task 1: An Attention-based Sentence Similarity Model",
author = "Zhuang, WenLi and
Chang, Ernie",
booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S17-2023",
doi = "10.18653/v1/S17-2023",
pages = "164--169",
abstract = "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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%0 Conference Proceedings
%T Neobility at SemEval-2017 Task 1: An Attention-based Sentence Similarity Model
%A Zhuang, WenLi
%A Chang, Ernie
%S Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
%D 2017
%8 aug
%I Association for Computational Linguistics
%C Vancouver, Canada
%F zhuang-chang-2017-neobility
%X 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.
%R 10.18653/v1/S17-2023
%U https://aclanthology.org/S17-2023
%U https://doi.org/10.18653/v1/S17-2023
%P 164-169
Markdown (Informal)
[Neobility at SemEval-2017 Task 1: An Attention-based Sentence Similarity Model](https://aclanthology.org/S17-2023) (Zhuang & Chang, SemEval 2017)
ACL