https://scholars.lib.ntu.edu.tw/handle/123456789/629163
標題: | Incorporating Peer Reviews and Rebuttal Counter-Arguments for Meta-Review Generation | 作者: | Wu, Po Cheng Yen, An Zi Huang, Hen Hsen HSIN-HSI CHEN |
關鍵字: | argument mining | counter-argument identification | meta-review generation | 公開日期: | 17-十月-2022 | 來源出版物: | International Conference on Information and Knowledge Management, Proceedings | 摘要: | 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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/629163 | ISBN: | 9781450392365 | DOI: | 10.1145/3511808.3557360 |
顯示於: | 資訊工程學系 |
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