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  4. Incorporating Peer Reviews and Rebuttal Counter-Arguments for Meta-Review Generation
 
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Incorporating Peer Reviews and Rebuttal Counter-Arguments for Meta-Review Generation

Journal
International Conference on Information and Knowledge Management, Proceedings
ISBN
9781450392365
Date Issued
2022-10-17
Author(s)
Wu, Po Cheng
Yen, An Zi
Huang, Hen Hsen
HSIN-HSI CHEN  
DOI
10.1145/3511808.3557360
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/629163
URL
https://api.elsevier.com/content/abstract/scopus_id/85140830746
Abstract
Peer review is an essential part of the scientific process in which the research papers are assessed by several reviewers. The author rebuttal phase, which is held at most top conferences, provides an opportunity for the authors to defend their work against the arguments made by the reviewers. The strengths and the weaknesses pointed out by the reviewers, as well as the authors' responses, will be evaluated by the area chair. The final decisions generally accompany meta-reviews regarding the reason for acceptance/rejection. Previous research has studied the generation of meta-review using transformer-based summarization models. However, few of them consider the rebuttals' content and the interaction between reviews and rebuttals' arguments, where the argumentation persuasiveness plays an important role in affecting the final decision. To generate a comprehensive meta-review that well organizes reviewers' opinions and authors' responses, we present a novel generation model that is capable of explicitly modeling the complicated argumentation structure from not only arguments between the reviewers and the authors but also the inter-reviewer discussions. Experimental results show that our model outperforms baselines in terms of both automatic evaluation and human evaluation, demonstrating the effectiveness of our approach.
Subjects
argument mining | counter-argument identification | meta-review generation
SDGs

[SDGs]SDG16

Type
conference paper

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