@inproceedings{celikyilmaz2018deep,
author = {Celikyilmaz, Asli and Bosselut, Antoine and He, Xiaodong and Choi, Yejin},
title = {Deep Communicating Agents for Abstractive Summarization},
booktitle = {2018 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2018)},
year = {2018},
month = {July},
abstract = {We present deep communicating agents in an encoder-decoder architecture to address the challenges of representing a long document for abstractive summarization. With deep communicating agents, the task of encoding a long text is divided across multiple collaborating agents, each in charge of a subsection of the input text. These encoders are connected to a single decoder, trained end-to-end using reinforcement learning to generate a focused and coherent summary. Empirical results demonstrate that multiple communicating encoders lead to a higher quality summary compared to several strong baselines, including those based on a single encoder or multiple non-communicating encoders.},
url = {http://approjects.co.za/?big=en-us/research/publication/deep-communicating-agents-abstractive-summarization/},
edition = {2018 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2018)},
}