icml-review-process
Use when explaining or diagnosing the ICML review process, including OpenReview, reciprocal reviewing, reviewer/AC behavior, review dimensions, author response, one-round discussion, LLM-review policy, ethics flags, and public review records.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icml-review-process --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ICML Review Process Use this to reason about how ICML reviewers and ACs will process a submission. The point is not to forecast acceptance by score folklore; it is to identify the decision issue and response strategy. ## Process features - ICML uses OpenReview with double-blind review. - ICML 2026 aims for about three reviews per paper, though the number can vary. - Reviewers consider soundness, originality, significance, clarity, and whether rebuttal resolved their main concerns. - Authors get a response period and then one additional reviewer-author discussion round. - Reviewers and ACs may discuss privately; ACs synthesize conflicts and unresolved concerns. - Reviews and author-reviewer discussion for accepted papers are made public. - ICML 2026 uses a Policy A / Policy B framework for reviewer LLM use, with authors indicating whether their paper requires Policy A review. - Reciprocal reviewing links author behavior to reviewer obligations and policy compliance. ## Diagnosis workflow 1. Categorize each likely criticism by soundness, originality, significance, clarity, ethics, reproducibility, or policy. 2. Identify which criticism an AC can quote in a meta-review. 3. Separate
- Process features
- Diagnosis workflow
- Score-dimension to AC-leverage map
- Worked vignette: reading a split panel
- Output format
What does the icml-review-process skill do?
Use when explaining or diagnosing the ICML review process, including OpenReview, reciprocal reviewing, reviewer/AC behavior, review dimensions, author response, one-round discussion, LLM-review policy, ethics flags, and public review records.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icml-review-process --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.