Singh, ShrutiSingh, MayankGoyal, Pawan2025-08-282025-08-282021-08-01https://d8.irins.org/handle/IITG2025/19820Comparing research papers is a conventional method to demonstrate progress in experimental research. We present COMPARE, a taxonomy and a dataset of comparison discussions in peer reviews of research papers in the domain of experimental deep learning. From a thorough observation of a large set of review sentences, we build a taxonomy of categories in comparison discussions and present a detailed annotation scheme to analyze this. Overall, we annotate 117 reviews covering 1,800 sentences. We experiment with various methods to identify comparison sentences in peer reviews and report a maximum F1 Score of 0.49. We also pretrain two language models specifically on ML, NLP, and CV paper abstracts and reviews to learn informative representations of peer reviews.en-USCOMPARETaxonomyDatasetComparison DiscussionsPeer Reviewse-Printe-Print123456789/435