Understanding and Supporting Peer Review Using AI-reframed Positive Summary
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Abstract (arXiv)
While peer review enhances writing and research quality, harsh feedback can frustrate and demotivate authors. Hence, it is essential to explore how critiques should be delivered to motivate authors and enable them to keep iterating their work. In this study, we explored the impact of appending an automatically generated positive summary to the peer reviews of a writing task, alongside varying levels of overall evaluations (high vs. low), on authors' feedback reception, revision outcomes, and motivation to revise. Through a 2x2 online experiment with 137 participants, we found that adding an AI-reframed positive summary to otherwise harsh feedback increased authors' critique acceptance, whereas low overall evaluations of their work led to increased revision efforts. We discuss the implications of using AI in peer feedback, focusing on how AI-driven critiques can influence critique acceptance and support research communities in fostering productive and friendly peer feedback practices.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Mar 2025.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2026When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Makingcited by 2
- 2025Feed-O-Meter: Investigating AI-Generated Mentee Personas as Interactive Agents for Scaffolding Design Feedback Practicecited by 0
- 2026AICoFe: Implementation and Deployment of an AI-Based Collaborative Feedback System for Higher Educationcited by 0
- 2026AICoFe: Implementation and Deployment of an AI-Based Collaborative Feedback System for Higher Education6 May 2026
- 2026When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Making3 Feb 2026
- 2025Feed-O-Meter: Investigating AI-Generated Mentee Personas as Interactive Agents for Scaffolding Design Feedback Practice9 Sep 2025