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However, traditional review digestion processes present challenges such as time consumption, reading fatigue, and the requisite for comprehensive analytical skills. Prior research on review analysis often provides theoretical guidance with limited targeted support. Additionally, general text comprehension tools overlook the intricate nature of comprehensively understanding reviews and lack contextual assistance. To bridge this gap, we formulated research questions to explore the authors' concerns and methods for enhancing comprehension during the review digestion phase. Through interviews and the creation of storyboards, we developed ReviseMate, an interactive system designed to address the identified challenges. A controlled user study (N=31) demonstrated the superiority of ReviseMate over baseline methods, with positive feedback regarding user interaction. Subsequent field deployment (N=6) further validated the effectiveness of ReviseMate in real-world review digestion scenarios. These findings underscore the potential of interactive tools to significantly enhance the assimilation and integration of reviewer feedback during the manuscript review process.<\/jats:p>","DOI":"10.1145\/3757502","type":"journal-article","created":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T16:59:10Z","timestamp":1760633950000},"page":"1-44","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["ReviseMate: Exploring Contextual Support for Digesting STEM Paper Reviews"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1630-6279","authenticated-orcid":false,"given":"Yuansong","family":"Xu","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1933-1869","authenticated-orcid":false,"given":"Shuhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9025-3719","authenticated-orcid":false,"given":"Yijie","family":"Fan","sequence":"additional","affiliation":[{"name":"College of Computing and Data Science, Nanyang Technological University, Singapore, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3384-8304","authenticated-orcid":false,"given":"Shaohan","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5700-3136","authenticated-orcid":false,"given":"Zhenhui","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2249-0728","authenticated-orcid":false,"given":"Quan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2025,10,16]]},"reference":[{"issue":"2013","key":"e_1_2_1_1_1","first-page":"155","article-title":"2013. 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