@inproceedings{d397a355d1864f459a202b36e05ca0ad,
title = "Multi-task attention-based neural networks for implicit discourse relationship representation and identification",
abstract = "We present a novel multi-task attention-based neural network model to address implicit discourse relationship representation and identification through two types of representation learning, an attention-based neural network for learning discourse relationship representation with two arguments and a multi-task framework for learning knowledge from annotated and unannotated corpora. The extensive experiments have been performed on two benchmark corpora (i.e., PDTB and CoNLL-2016 datasets). Experimental results show that our proposed model outperforms the state-of-the-art systems on benchmark corpora.",
author = "Man Lan and Jianxiang Wang and Yuanbin Wu and Niu, \{Zheng Yu\} and Haifeng Wang",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics.; 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 ; Conference date: 09-09-2017 Through 11-09-2017",
year = "2017",
doi = "10.18653/v1/d17-1134",
language = "英语",
series = "EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "1299--1308",
booktitle = "EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings",
address = "澳大利亚",
}