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LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization (1906.01512v1)

Published 28 May 2019 in cs.CL

Abstract: 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.

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Authors (3)
  1. Tian Shi (13 papers)
  2. Ping Wang (289 papers)
  3. Chandan K. Reddy (64 papers)
Citations (15)