AI-generated text and plagiarism detection

MDPI uses AI tools to automatically detect textual overlap and potential plagiarism in submitted manuscripts. This forms part of its broader integrity-checking infrastructure.

DocuMark reframes AI detection for universities: students verify and disclose their own AI usage rather than being policed by unreliable detectors, giving educators clearer insight into authorship. Integrates with learning management systems.

Ethicality is MDPI’s submission-screening tool, in testing as of late 2024, for identifying AI-generated publications, self-citation and unrelated references.

The American Association for Cancer Research analysed 7,177 manuscripts submitted to its 10 journals and found 36% of abstracts contained at least some AI-generated text. Evidence suggested four times as many authors use AI as disclose it —…

iThenticate is a cloud-based plagiarism detection tool designed for researchers, publishers, and institutions to verify the originality of high-stakes documents such as manuscripts, grant proposals, and theses. It compares submitted content against an extensive database of scholarly articles,…

Morressier, a platform dedicated to transforming scholarly communications, partnered with Copyleaks to integrate automated detection of plagiarism and AI-generated text into their workflows. This integration aims to assist academic societies and publishers in identifying fraudulent submissions, potential plagiarism,…

Pangram Labs develops tools to help researchers, educators, and publishers verify the originality and authenticity of written work. As generative AI becomes a routine part of writing workflows, distinguishing human authorship from machine-generated text has grown increasingly complex.Pangram’s…

Letters to the Editor submitted to one AACR journal were classified as human written, AI written, or of uncertain principal authorship. All AI-written letters were rejected without consideration until April 22, 2025, when an author was notified of…