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DISAPERE: A Dataset for Discourse Structure in Peer Review Discussions

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arxiv 2110.08520 v2 pith:U27MLJ2U submitted 2021-10-16 cs.CL

classification cs.CL
keywords reviewdisaperediscourseannotatedauthorsdatasetfurtherpeer
verification ladder T0 review T1 audit T2 compute T3 formal
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At the foundation of scientific evaluation is the labor-intensive process of peer review. This critical task requires participants to consume vast amounts of highly technical text. Prior work has annotated different aspects of review argumentation, but discourse relations between reviews and rebuttals have yet to be examined. We present DISAPERE, a labeled dataset of 20k sentences contained in 506 review-rebuttal pairs in English, annotated by experts. DISAPERE synthesizes label sets from prior work and extends them to include fine-grained annotation of the rebuttal sentences, characterizing their context in the review and the authors' stance towards review arguments. Further, we annotate every review and rebuttal sentence. We show that discourse cues from rebuttals can shed light on the quality and interpretation of reviews. Further, an understanding of the argumentative strategies employed by the reviewers and authors provides useful signal for area chairs and other decision makers.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. OpenReview Should be Protected and Leveraged as a Community Asset for Research in the Era of Large Language Models

    cs.CY 2025-05 conditional novelty 4.0 of 10

    The paper advocates protecting and leveraging OpenReview's peer review corpus as a community asset for LLM-based review assistance, benchmarks, and alignment.

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