Skills Artificial Intelligence Crafting ICML Rebuttal Responses

Crafting ICML Rebuttal Responses

v20260724
icml-author-response
A comprehensive guide for authors on drafting strategic, anonymous rebuttals and discussion replies for top-tier Machine Learning conferences like ICML. Learn how to triage reviewer objections by focusing on soundness, originality, significance, clarity, ethics, and reproducibility, adhering strictly to double-blind review constraints and maximizing impact in limited discussion rounds.
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Overview

ICML Author Response

Use this after initial ICML reviews arrive. The response should clarify and correct; it cannot rely on uploading a revised paper during the feedback period.

ICML response model

ICML 2026 author instructions state that authors can respond after initial reviews, that reviewers see those responses after the response period, and that reviewers and authors may then have one additional communication round. Responses must remain anonymous and should not contain non-anonymized URLs, personal websites, or shortened URLs. Reviewer instructions tell reviewers to explain whether the rebuttal changed their final recommendation.

Triage logic

  • Prioritize objections that affect soundness, originality, significance, clarity, ethics, or reproducibility.
  • Answer the AC's likely decision question, not every minor reviewer note.
  • Treat contradictions between reviewers as a chance to give the AC a clean synthesis.
  • Use new analyses sparingly and only to clarify an existing claim.
  • Keep all links anonymous and policy-compliant. Reviewers are not expected to follow external URLs in responses.

Drafting pattern

  1. Open with the central correction or concession.
  2. Refer to exact paper sections, appendix items, figures, tables, or supplement files.
  3. State what will change in camera-ready only if the paper is accepted.
  4. Maintain a professional, concise tone.
  5. Avoid identity leakage, score arguments, and broad promises.

Objection-to-response routing

ICML gives one response window plus one discussion round, so spend words on what an AC can quote, not on every minor note.

Reviewer objection Best ICML response move
"Assumptions do not match the experiments" Concede the regime, point to the in-regime figure, state the camera-ready clarification
"Missing tuned baseline" Supply a single decisive table row from a feasible run
"Unclear novelty vs concurrent work" Restate the one-line technical delta and the appendix PDF
"Reproducibility unclear" Cite the exact supplement command and seed

Worked vignette: defending the optimizer paper

Reviewer 2 says the convergence proof assumes bounded variance that ImageNet training violates. The strongest response opens with the concession, narrows the theoretical claim to the stated regime, adds a small plot showing the rate still tracks empirically where assumptions hold, and promises only a camera-ready wording fix. It does not argue the score or upload a revised PDF, both of which the ICML response model disallows.

Output format

[Priority issue] <reviewer/AC concern>
[Decision dimension] soundness / originality / significance / clarity / ethics / reproducibility
[Draft response] <ICML-ready anonymous text>
[Evidence anchor] <paper/appendix/supplement item>
[Discussion follow-up] <one possible reply if reviewer pushes back>
Info
Name icml-author-response
Version v20260724
Size 3.29KB
Updated At 2026-07-28
Language