AAAI Review Process

SkillDev tools

This skill gives your AI a clear picture of AAAI's two-phase review process so it can explain each stage and help you plan around it. It covers Phase 1 rejection risk, Phase 2 additional reviews, the AI-assisted review pilot, author feedback, SPC/AC discussion, and how final decisions are reached.

Available today. Use it from your connected AI after setup.

After adding it, ask your AI to walk you through the AAAI review process or to help you plan around a specific stage, such as Phase 1 risk or author feedback.

Then ask your AI: use the AAAI Review Process skill

What your AI can do with it

  • Explain how AAAI's two-phase review process works
  • Help you plan around Phase 1 rejection risk
  • Describe what happens in Phase 2, including additional reviews
  • Explain the AI-assisted review pilot
  • Clarify how author feedback, SPC/AC discussion, and final decisions fit together

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in AAAI-Skills/skills/aaai-review-process/SKILL.md and read by ahel’s review.

Use this to plan around AAAI review rather than treating it as a generic OpenReview rebuttal. Reopen the current review-process page and author FAQ before advising on timing or strategy.

Process model

  • AAAI main technical track uses double-blind reviewing.
  • AAAI-27 uses a two-phase review process. Phase 1 allocates three reviewers — two human reviews supplemented by one non-decisional AI-generated review. Papers with sufficiently negative reviews are rejected before author feedback (AAAI-27: notified 2026-09-24).
  • Papers continuing to Phase 2 receive additional reviews, up to five in total, and one author feedback phase (AAAI-27: 2026-10-19 to 10-25, final decisions 2026-11-30). Phase 2 reviewers are not shown the Phase 1 reviews until they have submitted their own — so a Phase 2 review is an independent read, not a reaction to the earlier ones.
  • Final decisions were made through reviewer discussion and senior program committee oversight, not by the AI review.
  • Author feedback is short and constrained; it is mainly for correcting misunderstandings, not replacing the paper.

Author strategy

  • Reduce Phase 1 reject risk before submission by making contribution, evidence, and checklist compliance obvious.
  • When reviews arrive, distinguish human-review claims, AI-review errors, and AC/SPC decision questions.
  • Use rebuttal to resolve the highest-impact factual issue under the character limit.
  • Do not attack the AI review. Correct it when it contains consequential false statements.
  • Avoid new experiments in rebuttal; use submitted evidence and camera-ready promises sparingly.

Stage-by-stage decision map

AAAI's pipeline differs from a single-round OpenReview venue, so plan actions per stage rather than treating every signal as a rebuttal opportunity.

StageWhat is happeningAuthor leverage
Pre-submissionPhase-1 bar is set by clarity and checklistmaximal: fix the paper itself
Phase 1human reviews plus advisory AI reviewnone yet; summary reject possible
Phase 2additional reviews, one feedback roundone short response, no new results
Discussionreviewers and SPC/AC weigh feedbackindirect: a clean correction can swing it
DecisionSPC/AC oversight, not the AI reviewarchive everything for appeal or journal

Why papers die in Phase 1

Because the reviewer pool is large and submission volume is high, clearly-below-bar papers are cut early to protect later effort. Common triggers: an unreadable first page, a contribution a non-specialist cannot place, a checklist that contradicts the paper, or evidence too thin to trust. None of these can be repaired after the Phase-1 cut, so they must be eliminated before submission.

Worked vignette

An NLP paper with strong results buries its contribution under three pages of setup. A Phase-1 reviewer from a planning background cannot find the AI claim and scores it a reject; the paper never reaches feedback. The fix belongs entirely pre-submission: a first-page contribution statement and a checklist that matches the experiments, so the broad-AI reviewer can place and trust it fast.

Output format

[Stage] pre-submission / Phase 1 / Phase 2 / rebuttal / discussion / decision
[Decision risk] summary reject / borderline / likely accept / ethics-policy risk
[Best action] revise before submission / rebut / clarify evidence / escalate
[AI-review handling] ignore / correct / cite submitted evidence
[Rationale] <why this fits AAAI process>

Signals

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Catalog kind
skill
Gateway key
aaai-review-process
Source
github.com/brycewang-stanford/awesome-journal-skills