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Break long journal papers into smaller publishable units
  • Here is an interesting suggestion from the field of biomedicine, to address the gradually increasing length of typical journal papers:


    In machine learning (and much of computer science), there is a venue for smaller publishable units: peer-reviewed conference papers.  However, these have their own weaknesses (e.g., one-shot reviewing), and despite the shorter format (typically 8-9 pages), reviewers still push for a "complete story" to emerge.  What if we focused conference papers on single experiments and results?  Or published short-form journal papers (where a complete review/revision cycle can be performed)?  Would there be increased value and readability, or too much fragmentation?  Is this relevant for ML?

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