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PreprintsTechnical ReportNot peer reviewed

Reproducibility-Checklist Compliance in Machine-Learning Papers: A technical report on what authors state and what they release

Ingrid Novak, Kofi Mensah

Version 1 · 27 July 2026 · 10.xxxx/ctm.pp.2026.0002

Many machine-learning venues now require authors to complete a reproducibility checklist. We audited 240 papers that ticked the item “code is provided” and checked whether the linked repositories existed, ran and reproduced the headline table. 87% had a reachable repository, 58% contained instructions sufficient to run training or evaluation, and 31% reproduced the headline result within the reported variance. Compliance was higher for papers reporting variance across seeds. We recommend checks that can be automated at submission time.

Abstract PDF 2,455 9314 cited
BooksHandbook

Open Research Data in Machine Learning: A handbook

Fatima Zahra El Idrissi, Ravi Menon, Ingrid Novak

1st edition · 186 pages · ISBN 978-0-00-100003-6 · 24 April 2026 · 10.xxxx/ctm.bk.2026.0003

A step-by-step handbook for sharing datasets, code and models so that others can find, cite and reuse them. It covers licences, documentation, identifiers, repositories, privacy, and long-term preservation, with checklists that can be adopted by labs and venues.

Read book PDF 3,610 1,9303 cited