CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization

Lei Li, Yang Xie, Wei Liu, Yinan Liu, Yafei Jiang, Siya Qi, Xingyuan Li


Abstract
Our system participates in two shared tasks, CL-SciSumm 2020 and LongSumm 2020. In the CL-SciSumm shared task, based on our previous work, we apply more machine learning methods on position features and content features for facet classification in Task1B. And GCN is introduced in Task2 to perform extractive summarization. In the LongSumm shared task, we integrate both the extractive and abstractive summarization ways. Three methods were tested which are T5 Fine-tuning, DPPs Sampling, and GRU-GCN/GAT.
Anthology ID:
2020.sdp-1.25
Volume:
Proceedings of the First Workshop on Scholarly Document Processing
Month:
November
Year:
2020
Address:
Online
Editors:
Muthu Kumar Chandrasekaran, Anita de Waard, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Eduard Hovy, Petr Knoth, David Konopnicki, Philipp Mayr, Robert M. Patton, Michal Shmueli-Scheuer
Venue:
sdp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
225–234
Language:
URL:
https://aclanthology.org/2020.sdp-1.25
DOI:
10.18653/v1/2020.sdp-1.25
Bibkey:
Cite (ACL):
Lei Li, Yang Xie, Wei Liu, Yinan Liu, Yafei Jiang, Siya Qi, and Xingyuan Li. 2020. CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization. In Proceedings of the First Workshop on Scholarly Document Processing, pages 225–234, Online. Association for Computational Linguistics.
Cite (Informal):
CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization (Li et al., sdp 2020)
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PDF:
https://aclanthology.org/2020.sdp-1.25.pdf
Video:
 https://slideslive.com/38940743