@inproceedings{chandrasekaran-etal-2020-overview,
title = "Overview of the First Workshop on Scholarly Document Processing ({SDP})",
author = "Chandrasekaran, Muthu Kumar and
Feigenblat, Guy and
Freitag, Dayne and
Ghosal, Tirthankar and
Hovy, Eduard and
Mayr, Philipp and
Shmueli-Scheuer, Michal and
de Waard, Anita",
editor = "Chandrasekaran, Muthu Kumar and
de Waard, Anita and
Feigenblat, Guy and
Freitag, Dayne and
Ghosal, Tirthankar and
Hovy, Eduard and
Knoth, Petr and
Konopnicki, David and
Mayr, Philipp and
Patton, Robert M. and
Shmueli-Scheuer, Michal",
booktitle = "Proceedings of the First Workshop on Scholarly Document Processing",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.sdp-1.1/",
doi = "10.18653/v1/2020.sdp-1.1",
pages = "1--6",
abstract = "Next to keeping up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. To address these challenges, computational work on enhancing search, summarization, and analysis of scholarly documents has flourished. However, the various strands of research on scholarly document processing remain fragmented. To reach to the broader NLP and AI/ML community, pool distributed efforts and enable shared access to published research, we held the 1st Workshop on Scholarly Document Processing at EMNLP 2020 as a virtual event. The SDP workshop consisted of a research track (including a poster session), two invited talks and three Shared Tasks (CL-SciSumm, Lay-Summ and LongSumm), geared towards easier access to scientific methods and results. \textbf{Website}: \url{https://ornlcda.github.io/SDProc}"
}
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<abstract>Next to keeping up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. To address these challenges, computational work on enhancing search, summarization, and analysis of scholarly documents has flourished. However, the various strands of research on scholarly document processing remain fragmented. To reach to the broader NLP and AI/ML community, pool distributed efforts and enable shared access to published research, we held the 1st Workshop on Scholarly Document Processing at EMNLP 2020 as a virtual event. The SDP workshop consisted of a research track (including a poster session), two invited talks and three Shared Tasks (CL-SciSumm, Lay-Summ and LongSumm), geared towards easier access to scientific methods and results. Website: https://ornlcda.github.io/SDProc</abstract>
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%0 Conference Proceedings
%T Overview of the First Workshop on Scholarly Document Processing (SDP)
%A Chandrasekaran, Muthu Kumar
%A Feigenblat, Guy
%A Freitag, Dayne
%A Ghosal, Tirthankar
%A Hovy, Eduard
%A Mayr, Philipp
%A Shmueli-Scheuer, Michal
%A de Waard, Anita
%Y Chandrasekaran, Muthu Kumar
%Y de Waard, Anita
%Y Feigenblat, Guy
%Y Freitag, Dayne
%Y Ghosal, Tirthankar
%Y Hovy, Eduard
%Y Knoth, Petr
%Y Konopnicki, David
%Y Mayr, Philipp
%Y Patton, Robert M.
%Y Shmueli-Scheuer, Michal
%S Proceedings of the First Workshop on Scholarly Document Processing
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F chandrasekaran-etal-2020-overview
%X Next to keeping up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. To address these challenges, computational work on enhancing search, summarization, and analysis of scholarly documents has flourished. However, the various strands of research on scholarly document processing remain fragmented. To reach to the broader NLP and AI/ML community, pool distributed efforts and enable shared access to published research, we held the 1st Workshop on Scholarly Document Processing at EMNLP 2020 as a virtual event. The SDP workshop consisted of a research track (including a poster session), two invited talks and three Shared Tasks (CL-SciSumm, Lay-Summ and LongSumm), geared towards easier access to scientific methods and results. Website: https://ornlcda.github.io/SDProc
%R 10.18653/v1/2020.sdp-1.1
%U https://aclanthology.org/2020.sdp-1.1/
%U https://doi.org/10.18653/v1/2020.sdp-1.1
%P 1-6
Markdown (Informal)
[Overview of the First Workshop on Scholarly Document Processing (SDP)](https://aclanthology.org/2020.sdp-1.1/) (Chandrasekaran et al., sdp 2020)
ACL
- Muthu Kumar Chandrasekaran, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Eduard Hovy, Philipp Mayr, Michal Shmueli-Scheuer, and Anita de Waard. 2020. Overview of the First Workshop on Scholarly Document Processing (SDP). In Proceedings of the First Workshop on Scholarly Document Processing, pages 1–6, Online. Association for Computational Linguistics.