Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP)

Arman Cohan, Guy Feigenblat, Tirthankar Ghosal, Michal Shmueli-Scheuer


Abstract
We present the main findings of MuP 2022 shared task, the first shared task on multi-perspective scientific document summarization. The task provides a testbed representing challenges for summarization of scientific documents, and facilitates development of better models to leverage summaries generated from multiple perspectives. We received 139 total submissions from 9 teams. We evaluated submissions both by automated metrics (i.e., Rouge) and human judgments on faithfulness, coverage, and readability which provided a more nuanced view of the differences between the systems. While we observe encouraging results from the participating teams, we conclude that there is still significant room left for improving summarization leveraging multiple references. Our dataset is available at https://github.com/allenai/mup.
Anthology ID:
2022.sdp-1.32
Volume:
Proceedings of the Third Workshop on Scholarly Document Processing
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
sdp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
263–267
Language:
URL:
https://aclanthology.org/2022.sdp-1.32
DOI:
Bibkey:
Cite (ACL):
Arman Cohan, Guy Feigenblat, Tirthankar Ghosal, and Michal Shmueli-Scheuer. 2022. Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP). In Proceedings of the Third Workshop on Scholarly Document Processing, pages 263–267, Gyeongju, Republic of Korea. Association for Computational Linguistics.
Cite (Informal):
Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP) (Cohan et al., sdp 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.sdp-1.32.pdf
Code
 allenai/mup