@inproceedings{gidiotis-etal-2020-auth,
title = "{AUTH} @ {CLS}ci{S}umm 20, {L}ay{S}umm 20, {L}ong{S}umm 20",
author = "Gidiotis, Alexios and
Stefanidis, Stefanos and
Tsoumakas, Grigorios",
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-1.28",
doi = "10.18653/v1/2020.sdp-1.28",
pages = "251--260",
abstract = "We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020. Our approaches to the tasks are focused on exploiting large Transformer models pre-trained on huge corpora and adapting them to the different shared tasks. For tasks 1A and 1B of CL-SciSumm we are using different variants of the BERT model to tackle the tasks of {``}cited text span{''} and {``}facet{''} identification. For the summarization tasks 2 of CL-SciSumm, LaySumm and LongSumm we make use of different variants of the PEGASUS model, with and without fine-tuning, adapted to the nuances of each one of those particular tasks.",
}
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<abstract>We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020. Our approaches to the tasks are focused on exploiting large Transformer models pre-trained on huge corpora and adapting them to the different shared tasks. For tasks 1A and 1B of CL-SciSumm we are using different variants of the BERT model to tackle the tasks of “cited text span” and “facet” identification. For the summarization tasks 2 of CL-SciSumm, LaySumm and LongSumm we make use of different variants of the PEGASUS model, with and without fine-tuning, adapted to the nuances of each one of those particular tasks.</abstract>
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%0 Conference Proceedings
%T AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20
%A Gidiotis, Alexios
%A Stefanidis, Stefanos
%A Tsoumakas, Grigorios
%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 gidiotis-etal-2020-auth
%X We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020. Our approaches to the tasks are focused on exploiting large Transformer models pre-trained on huge corpora and adapting them to the different shared tasks. For tasks 1A and 1B of CL-SciSumm we are using different variants of the BERT model to tackle the tasks of “cited text span” and “facet” identification. For the summarization tasks 2 of CL-SciSumm, LaySumm and LongSumm we make use of different variants of the PEGASUS model, with and without fine-tuning, adapted to the nuances of each one of those particular tasks.
%R 10.18653/v1/2020.sdp-1.28
%U https://aclanthology.org/2020.sdp-1.28
%U https://doi.org/10.18653/v1/2020.sdp-1.28
%P 251-260
Markdown (Informal)
[AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20](https://aclanthology.org/2020.sdp-1.28) (Gidiotis et al., sdp 2020)
ACL
- Alexios Gidiotis, Stefanos Stefanidis, and Grigorios Tsoumakas. 2020. AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20. In Proceedings of the First Workshop on Scholarly Document Processing, pages 251–260, Online. Association for Computational Linguistics.