Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment
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Abstract (arXiv)
We consider the issue of strategic behaviour in various peer-assessment tasks, including peer grading of exams or homeworks and peer review in hiring or promotions. When a peer-assessment task is competitive (e.g., when students are graded on a curve), agents may be incentivized to misreport evaluations in order to improve their own final standing. Our focus is on designing methods for detection of such manipulations. Specifically, we consider a setting in which agents evaluate a subset of their peers and output rankings that are later aggregated to form a final ordering. In this paper, we investigate a statistical framework for this problem and design a principled test for detecting strategic behaviour. We prove that our test has strong false alarm guarantees and evaluate its detection ability in practical settings. For this, we design and execute an experiment that elicits strategic behaviour from subjects and release a dataset of patterns of strategic behaviour that may be of independent interest. We then use the collected data to conduct a series of real and semi-synthetic evaluations that demonstrate a strong detection power of our test.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Oct 2020.
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Citing papers per year: 2021: 4; 2022: 4; 2023: 1; 2024: 3; 2025: 1; 2026: 1.
14 papers.
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- 2023ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewingcited by 118
- 2024What Can Natural Language Processing Do for Peer Review?cited by 24
- 2022Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyondcited by 12
- 2025Insights from the ICLR Peer Review and Rebuttal Processcited by 8
- 2024On the Detection of Reviewer-Author Collusion Rings From Paper Biddingcited by 7
- 2021Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Designcited by 6
- 2022Strategyproofing Peer Assessment via Partitioning: The Price in Terms of Evaluators' Expertisecited by 6
- 2021Least Square Calibration for Peer Reviewcited by 3
- 2021Peer Selection with Noisy Assessmentscited by 2
- 2024Enhancing Peer Review in Astronomy: A Machine Learning and Optimization Approach to Reviewer Assignments for ALMAcited by 2
- 2022Manipulation and Peer Mechanisms: A Surveycited by 1
- 2021Improving Peer Assessment with Graph Convolutional Networkscited by 0
- 2026Articulate Intuition or Genuine Analysis? Benchmarking Epistemic Reliability in LLM-as-a-Judge Peer Reviews12 Jul 2026
- 2025Insights from the ICLR Peer Review and Rebuttal Process19 Nov 2025
- 2024Enhancing Peer Review in Astronomy: A Machine Learning and Optimization Approach to Reviewer Assignments for ALMA13 Oct 2024
- 2024What Can Natural Language Processing Do for Peer Review?10 May 2024
- 2024On the Detection of Reviewer-Author Collusion Rings From Paper Bidding12 Feb 2024
- 2023ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing1 Jun 2023
- 2022No Agreement Without Loss: Learning and Social Choice in Peer Review3 Nov 2022
- 2022Manipulation and Peer Mechanisms: A Survey5 Oct 2022
- 2022Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyond27 Jan 2022
- 2022Strategyproofing Peer Assessment via Partitioning: The Price in Terms of Evaluators' Expertise25 Jan 2022
- 2021Improving Peer Assessment with Graph Convolutional Networks4 Nov 2021
- 2021Least Square Calibration for Peer Review25 Oct 2021
2 more
- 2023ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewingcited by 118
- 2024What Can Natural Language Processing Do for Peer Review?cited by 24
- 2022Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyondcited by 12
- 2025Insights from the ICLR Peer Review and Rebuttal Processcited by 8
- 2024On the Detection of Reviewer-Author Collusion Rings From Paper Biddingcited by 7
- 2021Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Designcited by 6
- 2022Strategyproofing Peer Assessment via Partitioning: The Price in Terms of Evaluators' Expertisecited by 6
- 2021Least Square Calibration for Peer Reviewcited by 3
- 2021Peer Selection with Noisy Assessmentscited by 2
- 2024Enhancing Peer Review in Astronomy: A Machine Learning and Optimization Approach to Reviewer Assignments for ALMAcited by 2
- 2022Manipulation and Peer Mechanisms: A Surveycited by 1
- 2021Improving Peer Assessment with Graph Convolutional Networkscited by 0
12 most cited of 14 All 14 (JSON)
- 2026Articulate Intuition or Genuine Analysis? Benchmarking Epistemic Reliability in LLM-as-a-Judge Peer Reviews12 Jul 2026
- 2025Insights from the ICLR Peer Review and Rebuttal Process19 Nov 2025
- 2024Enhancing Peer Review in Astronomy: A Machine Learning and Optimization Approach to Reviewer Assignments for ALMA13 Oct 2024
- 2024What Can Natural Language Processing Do for Peer Review?10 May 2024
- 2024On the Detection of Reviewer-Author Collusion Rings From Paper Bidding12 Feb 2024
- 2023ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing1 Jun 2023
- 2022No Agreement Without Loss: Learning and Social Choice in Peer Review3 Nov 2022
- 2022Manipulation and Peer Mechanisms: A Survey5 Oct 2022
- 2022Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyond27 Jan 2022
- 2022Strategyproofing Peer Assessment via Partitioning: The Price in Terms of Evaluators' Expertise25 Jan 2022
- 2021Improving Peer Assessment with Graph Convolutional Networks4 Nov 2021
- 2021Least Square Calibration for Peer Review25 Oct 2021
12 newest of 14 All 14 (JSON)