paper-with-me

Papers

Combating Collusion Rings is Hard but Possible

2021-12-14 · Niclas Boehmer, Robert Bredereck, André Nichterlein

A recent report of Littmann [Commun. ACM '21] outlines the existence and the fatal impact of collusion rings in academic peer reviewing. We introduce and analyze the problem Cycle-Free Reviewing that aims at finding a review assignment without the following kind of collusion ring: A sequence of reviewers each reviewing a paper authored by the next reviewer in the sequence (with the last reviewer reviewing a paper of the first), thus creating a review cycle where each reviewer gives favorable reviews. As a result, all papers in that cycle have a high chance of acceptance independent of their respective scientific merit. We observe that review assignments computed using a standard Linear Programming approach typically admit many short review cycles. On the negative side, we show that Cycle-Free Reviewing is NP-hard in various restricted cases (i.e., when every author is qualified to review all papers and one wants to prevent that authors review each other's or their own papers or when every author has only one paper and is only qualified to review few papers). On the positive side, among others, we show that, in some realistic settings, an assignment without any review cycles of small length always exists. This result also gives rise to an efficient heuristic for computing (weighted) cycle-free review assignments, which we show to be of excellent quality in practice.

📄 PDF Abstract BibTeX arXiv:2112.08444

Code (1)

n-boehmer/combating-collusion-rings-is-hard-but-possible 공식 구현

Similar Papers 제목 키워드 기반

On the Detection of Reviewer-Author Collusion Rings From Paper Bidding

2024-02-12 · Steven Jecmen, Nihar B. Shah, Fei Fang, Leman Akoglu

A major threat to the peer-review systems of computer science conferences is the existence of "collusion rings" between reviewers. In such collusion rings, reviewers who have also submitted their own papers to the confer…

Fraud Detectiontext similarity

Vulnerability of Text-Matching in ML/AI Conference Reviewer Assignments to Collusions

2024-12-09 · Jhih-Yi, Hsieh, aditi raghunathan, Nihar B. Shah

In the peer review process of top-tier machine learning (ML) and artificial intelligence (AI) conferences, reviewers are assigned to papers through automated methods. These assignment algorithms consider two main factors…

Text Matchingtext similarity

Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Models

2026-06-11 · Jianwei Fei, Yunshu Dai, Zhihua Xia, Xiaochun Cao 외 arxiv

Model fingerprinting, embedding user-specific identifiers (fingerprints) into generated outputs, has recently emerged as a popular solution to protect the intellectual property rights (IPR) of generative text-to-image (T…

Image Generation

Secret Collusion among Generative AI Agents: Multi-Agent Deception via Steganography

2024-02-12 · Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina 외

Recent capability increases in large language models (LLMs) open up applications in which groups of communicating generative AI agents solve joint tasks. This poses privacy and security challenges concerning the unauthor…

Optimal Collusion-Free Teaching

2019-03-10 · David Kirkpatrick, Hans U. Simon, Sandra Zilles

Formal models of learning from teachers need to respect certain criteria to avoid collusion. The most commonly accepted notion of collusion-freeness was proposed by Goldman and Mathias (1996), and various teaching models…