A growing concern within the machine learning research community is the lack of reproducible code accompanying submitted papers. Reviewers are increasingly encountering submissions with no code, or code that contains significant bugs, undermining the integrity of research findings. To address this, there's a push to implement stricter policies, such as desk-rejecting papers that do not include functional code, to incentivize transparency and reproducibility. AI
IMPACT Lack of reproducible code hinders scientific progress and trust in AI research findings.
RANK_REASON The item is a discussion/opinion piece about a trend in academic publishing, not a direct announcement or event.
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