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aaai-workflow

Use when planning an AAAI project timeline from topic selection through abstract, OpenReview submission, two-phase review, rebuttal, decision, camera-ready, registration, presentation, and public artifact release.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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AAAI Workflow

Use this as the project-management skill for an AAAI submission. Replace all dates with the current cycle's official timetable and work backwards from OpenReview cutoffs.

AAAI is a conference, not a journal: it has no standing editor-in-chief and no article-processing charge. The rotating leadership is the per-edition Program Chairs, and the cost model is registration fees, not APCs — at least one author must register at the in-person rate and present in person; AAAI-27 offers no remote option, and a paper without a registered presenter is removed before publication. The AAAI-27 chairs are not recorded in this pack: the AAAI-27 organizers URL still redirects to an older edition's roster, so no official page names them (the AAAI-26 chairs were Chad Jenkins and Matthew Taylor, and those appointments rotate). Re-check the current CFP and conference-organizers page rather than carrying a name or contact forward.

Milestones

  • Venue fit: choose Main Track, AI for Social Impact, AI Alignment, or another AAAI program.
  • Evidence lock: freeze contribution, baselines, ablations, checklist answers, and supplement.
  • Abstract deadline: submit real metadata, title, abstract, authors, subject areas, and conflicts.
  • Paper deadline: upload anonymous PDF, reproducibility checklist, supplement, and OpenReview fields.
  • Phase 1 risk check: ensure the paper can be understood quickly and does not look checklist-thin.
  • Review release: identify whether the paper is in Phase 2 and triage reviews, including AI review if present.
  • Rebuttal: draft a compact, no-URL, no-new-results response using only submitted evidence.
  • Decision: archive reviews, rebuttal, decision, and final submitted version.
  • Acceptance: submit source files, copyright, camera-ready PDF, registration, presentation plan, and public artifacts.

Operating rules

  • Keep a single checklist for page limit, anonymity, supplement integrity, author limit, and multiple-submission policy.
  • Run a fresh anonymity audit after every PDF or ZIP export.
  • Verify ZIP files open and reproduce expected paths before submission.
  • Do not leave core evidence to rebuttal.

Backward-planning table

Because AAAI runs a two-phase review with hard OpenReview cutoffs and no second feedback round, the timeline is unforgiving. Anchor each gate to the prior one and to the official date, not a guess.

GateDepends onSlip consequence
Abstract deadlinetitle, authors, conflicts lockedcannot submit the paper
Paper deadlineanonymous PDF, checklist, supplementsummary reject or no entry
Phase-1 cutclarity and checklist done earlyno feedback, paper dies
Feedback roundsubmitted evidence onlywasted on new-results bans
Camera-readyacceptance, copyright, registrationdropped from proceedings

Phase-1 readiness gate

Treat the Phase-1 cut as the real deadline, earlier than acceptance. Before the paper deadline, a non-specialist colleague should be able to state your contribution, find the evidence, and confirm the checklist matches the paper. If they cannot, the broad-AI reviewer will not either.

Worked vignette

A team plans to "finish experiments in rebuttal." The workflow flags this as fatal: AAAI bars new results at feedback and may cut the paper in Phase 1 before feedback exists. The critical path moves to locking evidence and the checklist a week before the paper deadline, leaving the feedback window only for clarifying already-submitted material.

Output format

[Current stage] idea / experiments / writing / submission / Phase 1 / rebuttal / accepted
[Next official deadline] <date and source, or unknown>
[Critical path] <three tasks that determine readiness>
[Risk register] <page, anonymity, checklist, supplement, policy>
[Owner map] <task -> person or role>

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같은 저장소의 스킬

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

brycewang-stanford/Awesome-Journal-Skills1.3천2026년 9월 27일 업데이트

Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

brycewang-stanford/Awesome-Journal-Skills1.3천2026년 9월 27일 업데이트

Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

brycewang-stanford/Awesome-Journal-Skills1.3천2026년 9월 27일 업데이트

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

brycewang-stanford/Awesome-Journal-Skills1.3천2026년 9월 27일 업데이트

Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

brycewang-stanford/Awesome-Journal-Skills1.3천2026년 9월 27일 업데이트

Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

brycewang-stanford/Awesome-Journal-Skills1.3천2026년 9월 27일 업데이트

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