@inproceedings{vadapalli-etal-2018-science,
title = "When science journalism meets artificial intelligence : An interactive demonstration",
author = "Vadapalli, Raghuram and
Syed, Bakhtiyar and
Prabhu, Nishant and
Srinivasan, Balaji Vasan and
Varma, Vasudeva",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-2028",
doi = "10.18653/v1/D18-2028",
pages = "163--168",
abstract = "We present an online interactive tool that generates titles of blog titles and thus take the first step toward automating science journalism. Science journalism aims to transform jargon-laden scientific articles into a form that the common reader can comprehend while ensuring that the underlying meaning of the article is retained. In this work, we present a tool, which, given the title and abstract of a research paper will generate a blog title by mimicking a human science journalist. The tool makes use of a model trained on a corpus of 87,328 pairs of research papers and their corresponding blogs, built from two science news aggregators. The architecture of the model is a two-stage mechanism which generates blog titles. Evaluation using standard metrics indicate the viability of the proposed system.",
}
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%0 Conference Proceedings
%T When science journalism meets artificial intelligence : An interactive demonstration
%A Vadapalli, Raghuram
%A Syed, Bakhtiyar
%A Prabhu, Nishant
%A Srinivasan, Balaji Vasan
%A Varma, Vasudeva
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2018
%8 nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F vadapalli-etal-2018-science
%X We present an online interactive tool that generates titles of blog titles and thus take the first step toward automating science journalism. Science journalism aims to transform jargon-laden scientific articles into a form that the common reader can comprehend while ensuring that the underlying meaning of the article is retained. In this work, we present a tool, which, given the title and abstract of a research paper will generate a blog title by mimicking a human science journalist. The tool makes use of a model trained on a corpus of 87,328 pairs of research papers and their corresponding blogs, built from two science news aggregators. The architecture of the model is a two-stage mechanism which generates blog titles. Evaluation using standard metrics indicate the viability of the proposed system.
%R 10.18653/v1/D18-2028
%U https://aclanthology.org/D18-2028
%U https://doi.org/10.18653/v1/D18-2028
%P 163-168
Markdown (Informal)
[When science journalism meets artificial intelligence : An interactive demonstration](https://aclanthology.org/D18-2028) (Vadapalli et al., EMNLP 2018)
ACL