@inproceedings{xu-etal-2018-cross,
title = "Cross-Target Stance Classification with Self-Attention Networks",
author = "Xu, Chang and
Paris, C{\'e}cile and
Nepal, Surya and
Sparks, Ross",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-2123",
doi = "10.18653/v1/P18-2123",
pages = "778--783",
abstract = "In stance classification, the target on which the stance is made defines the boundary of the task, and a classifier is usually trained for prediction on the same target. In this work, we explore the potential for generalizing classifiers between different targets, and propose a neural model that can apply what has been learned from a source target to a destination target. We show that our model can find useful information shared between relevant targets which improves generalization in certain scenarios.",
}
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%0 Conference Proceedings
%T Cross-Target Stance Classification with Self-Attention Networks
%A Xu, Chang
%A Paris, Cécile
%A Nepal, Surya
%A Sparks, Ross
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F xu-etal-2018-cross
%X In stance classification, the target on which the stance is made defines the boundary of the task, and a classifier is usually trained for prediction on the same target. In this work, we explore the potential for generalizing classifiers between different targets, and propose a neural model that can apply what has been learned from a source target to a destination target. We show that our model can find useful information shared between relevant targets which improves generalization in certain scenarios.
%R 10.18653/v1/P18-2123
%U https://aclanthology.org/P18-2123
%U https://doi.org/10.18653/v1/P18-2123
%P 778-783
Markdown (Informal)
[Cross-Target Stance Classification with Self-Attention Networks](https://aclanthology.org/P18-2123) (Xu et al., ACL 2018)
ACL
- Chang Xu, Cécile Paris, Surya Nepal, and Ross Sparks. 2018. Cross-Target Stance Classification with Self-Attention Networks. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 778–783, Melbourne, Australia. Association for Computational Linguistics.