LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization

被引：0
作者：
Shi, Tian [1 ]
Wang, Ping [1 ]
Reddy, Chandan K. [1 ]
机构：
[1] Virginia Tech, Blacksburg, VA 24061 USA
来源：
NAACL HLT 2019: THE 2019 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES: PROCEEDINGS OF THE DEMONSTRATIONS SESSION | 2019年
基金：
美国国家科学基金会;
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Neural abstractive text summarization (NATS) has received a lot of attention in the past few years from both industry and academia. In this paper, we introduce an open-source toolkit, namely LeafNATS, for training and evaluation of different sequence-to-sequence based models for the NATS task, and for deploying the pre-trained models to real-world applications. The toolkit is modularized and extensible in addition to maintaining competitive performance in the NATS task. A live news blogging system has also been implemented to demonstrate how these models can aid blog/news editors by providing them suggestions of headlines and summaries of their articles.
引用
收藏
页码：66 / 71
页数：6
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