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        <title>To Attend or not to Attend: A Case Study on Syntactic Structures for Semantic Relatedness</title>
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    <abstract>With the recent success of Recurrent Neural Networks (RNNs) in Machine Translation (MT), attention mechanisms have become increasingly popular. The purpose of this paper is two-fold; firstly, we propose a novel attention model on Tree Long Short-Term Memory Networks (Tree-LSTMs), a tree-structured generalization of standard LSTM. Secondly, we study the interaction between attention and syntactic structures, by experimenting with three LSTM variants: bidirectional-LSTMs, Constituency Tree-LSTMs, and Dependency Tree-LSTMs. Our models are evaluated on two semantic relatedness tasks: semantic relatedness scoring for sentence pairs (SemEval 2012, Task 6 and SemEval 2014, Task 1) and paraphrase detection for question pairs (Quora, 2017).</abstract>
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%0 Conference Proceedings
%T To Attend or not to Attend: A Case Study on Syntactic Structures for Semantic Relatedness
%A Gupta, Amulya
%A Zhang, Zhu
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F gupta-zhang-2018-attend
%X With the recent success of Recurrent Neural Networks (RNNs) in Machine Translation (MT), attention mechanisms have become increasingly popular. The purpose of this paper is two-fold; firstly, we propose a novel attention model on Tree Long Short-Term Memory Networks (Tree-LSTMs), a tree-structured generalization of standard LSTM. Secondly, we study the interaction between attention and syntactic structures, by experimenting with three LSTM variants: bidirectional-LSTMs, Constituency Tree-LSTMs, and Dependency Tree-LSTMs. Our models are evaluated on two semantic relatedness tasks: semantic relatedness scoring for sentence pairs (SemEval 2012, Task 6 and SemEval 2014, Task 1) and paraphrase detection for question pairs (Quora, 2017).
%R 10.18653/v1/P18-1197
%U https://aclanthology.org/P18-1197
%U https://doi.org/10.18653/v1/P18-1197
%P 2116-2125

Markdown (Informal)

[To Attend or not to Attend: A Case Study on Syntactic Structures for Semantic Relatedness](https://aclanthology.org/P18-1197) (Gupta & Zhang, ACL 2018)

• To Attend or not to Attend: A Case Study on Syntactic Structures for Semantic Relatedness (Gupta & Zhang, ACL 2018)

ACL

• Amulya Gupta and Zhu Zhang. 2018. To Attend or not to Attend: A Case Study on Syntactic Structures for Semantic Relatedness. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2116–2125, Melbourne, Australia. Association for Computational Linguistics.