@inproceedings{zhang-litman-2018-co,
title = "Co-Attention Based Neural Network for Source-Dependent Essay Scoring",
author = "Zhang, Haoran and
Litman, Diane",
editor = "Tetreault, Joel and
Burstein, Jill and
Kochmar, Ekaterina and
Leacock, Claudia and
Yannakoudakis, Helen",
booktitle = "Proceedings of the Thirteenth Workshop on Innovative Use of {NLP} for Building Educational Applications",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-0549",
doi = "10.18653/v1/W18-0549",
pages = "399--409",
abstract = "This paper presents an investigation of using a co-attention based neural network for source-dependent essay scoring. We use a co-attention mechanism to help the model learn the importance of each part of the essay more accurately. Also, this paper shows that the co-attention based neural network model provides reliable score prediction of source-dependent responses. We evaluate our model on two source-dependent response corpora. Results show that our model outperforms the baseline on both corpora. We also show that the attention of the model is similar to the expert opinions with examples.",
}
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%0 Conference Proceedings
%T Co-Attention Based Neural Network for Source-Dependent Essay Scoring
%A Zhang, Haoran
%A Litman, Diane
%Y Tetreault, Joel
%Y Burstein, Jill
%Y Kochmar, Ekaterina
%Y Leacock, Claudia
%Y Yannakoudakis, Helen
%S Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F zhang-litman-2018-co
%X This paper presents an investigation of using a co-attention based neural network for source-dependent essay scoring. We use a co-attention mechanism to help the model learn the importance of each part of the essay more accurately. Also, this paper shows that the co-attention based neural network model provides reliable score prediction of source-dependent responses. We evaluate our model on two source-dependent response corpora. Results show that our model outperforms the baseline on both corpora. We also show that the attention of the model is similar to the expert opinions with examples.
%R 10.18653/v1/W18-0549
%U https://aclanthology.org/W18-0549
%U https://doi.org/10.18653/v1/W18-0549
%P 399-409
Markdown (Informal)
[Co-Attention Based Neural Network for Source-Dependent Essay Scoring](https://aclanthology.org/W18-0549) (Zhang & Litman, BEA 2018)
ACL