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  2. Peer Review in Computer Science: good, bad & broken
  3. Natural Language Processing
  4. 🚨 [New ACL ARR Review Issue Reporting System]

🚨 [New ACL ARR Review Issue Reporting System]

Scheduled Pinned Locked Moved Natural Language Processing
emnlp2025area chairaclreview issuearrbiasedpeer reviewdecision
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  • SylviaS Offline
    SylviaS Offline
    Sylvia
    Super Users
    wrote last edited by
    #1

    Heads Up, ACL/EMNLP Authors! πŸ“

    ACL ARR has just launched a new review issue reporting system in OpenReview, which is now available after the author discussion period. The aim is to improve review quality and provide authors with a direct, formal way to flag serious procedural issues with their reviews.

    Review Issue Report Form

    πŸ”‘ Key Details & How It Works

    • 12 Specific Issue Types:
      You can now report issues using clear categories, including:

      • Not Specific
      • Reviewer Heuristics
      • Score Mismatch
      • Unprofessional Tone
      • Expertise
      • Type/Contribution Mismatch
      • Missing/Uninformative Review
      • Late Review
      • Unreasonable Requests
      • Non-Response to Author
      • Other Technical Issues
    • Justification Required:
      For each issue, you must provide a concise, evidence-based justification, citing the specific review section and corresponding issue code (e.g., β€œI2. The reviewer states […]. We believe that this corresponds to review issue type I2, because […]”).

    • Implications:
      Reports will be visible to ACs, who will consider them in meta-reviews and for process improvements. They’ll also be used for future analysis of review quality.

    • Deadline:
      Submit review issue reports by 8 July 2025 AOE for this cycle!

    • More Info:
      See full details and screenshots here: https://aclrollingreview.org/authors#step2.2


    πŸ’‘ Why This Matters

    • Gives authors a voice in review quality control.
    • Supports better accountability and fairness in peer review.
    • Data from these reports will help the community improve the process for everyone.

    Have you encountered a review that’s vague, biased, unqualified, or late? Use the new system to make it count!

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