Peer review is central to scientific publishing, yet reviewers frequently include claims that are subjective, rhetorical, or misaligned with the submitted work. Assessing whether review statements are factual and verifiable is crucial for fairness and accountability. At the scale of modern conferences and journals, manually inspecting the grounding of such claims is infeasible. We present Peerispect, an interactive system that operationalizes claim-level verification in peer reviews by extracting check-worthy claims from peer reviews, retrieving relevant evidence from the manuscript, and verifying the claims through natural language inference. Results are presented through a visual interface that highlights evidence directly in the paper, enabling rapid inspection and interpretation. Peerispect is designed as a modular Information Retrieval (IR) pipeline, supporting alternative retrievers, rerankers, and verifiers, and is intended for use by reviewers, authors, and program committees. We demonstrate Peerispect through a live, publicly available demo (https://app.reviewer.ly/app/peerispect) and API services (https://github.com/Reviewerly-Inc/Peerispect), accompanied by a video tutorial (https://www.youtube.com/watch?v=pc9RkvkUh14).

翻译：同行评审是科学出版的核心环节，然而评审者经常提出带有主观性、修辞性，或与所评稿件内容不符的声明。评估评审陈述是否为基于事实且可验证的，这对保证公平性和问责制至关重要。在现代会议和期刊的规模下，人工检查这些声明的依据是不可行的。我们提出了Peerispect，一个交互式系统，它通过从同行评审中提取值得核查的声明、从手稿中检索相关证据、并通过自然语言推理验证声明，将同行评审中的声明级验证操作化。结果通过一个视觉界面呈现，该界面直接在论文中高亮显示证据，从而实现快速的审查和解读。Peerispect被设计为一个模块化的信息检索（IR）流水线，支持替代的检索器、重排序器和验证器，旨在供评审者、作者和程序委员会使用。我们通过一个公开可用的实时演示（https://app.reviewer.ly/app/peerispect）、API服务（https://github.com/Reviewerly-Inc/Peerispect）以及一个配套的视频教程（https://www.youtube.com/watch?v=pc9RkvkUh14）来展示Peerispect。