본문으로 건너뛰기
cccskills
무료GitHub에 공개

aistats-submission

Use when auditing an AISTATS submission for OpenReview readiness, abstract/full-paper deadlines, the 8-page submission body, double-blind anonymity, supplementary material, reproducibility checklist, dual-submission policy, reviewer volunteer requirements, desk-reject triggers, and final-week submission sequencing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

실행 점수 미검증

설치 방법 보기

포함된 파일(1)

  • SKILL.md3.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

AISTATS Submission

Use this for an AISTATS paper submission audit. Reopen the current Call for Papers, OpenReview group, style files, FAQ, and proceedings instructions before giving deadline-ready advice.

Submission audit

  • Confirm the target is the main AISTATS conference, not a workshop or tutorial.
  • Verify OpenReview profiles, conflicts, subject areas, title, abstract, author list, and reviewer-volunteer obligations before the abstract and full-paper deadlines.
  • Apply the current style file without spacing, margin, font, or bibliography hacks. AISTATS 2026 used 8 pages of main text for submission, excluding references and appendices.
  • Submit supplementary material by the current supplement deadline. In 2026 this was a separate deadline after the main paper deadline, and supplementary uploads were optional but had to remain anonymous.
  • Include or complete the reproducibility checklist if the current cycle requires it.
  • Enforce double-blind anonymity in paper text, appendix, supplement, code/data, file names, metadata, repository links, acknowledgements, grants, and self-citations.
  • Check concurrent-submission rules and prior-publication status. Do not put the same work under review at another archival venue when AISTATS forbids it.

Blocking risks

  • Late abstract or full-paper upload.
  • Overlength main text or modified style.
  • Non-anonymized supplement, metadata, repository, or appendix.
  • Missing reproducibility checklist or required OpenReview fields.
  • Dual submission to another archival venue.
  • Unclear statistical evidence, weak baselines, or missing uncertainty analysis.

Desk-reject and triage table

TriggerSeverity at AISTATSRepair window
Overlength main textDesk rejectNone after the deadline
Style-file tamperingDesk reject or chair flagNone
Identity leak in PDF or supplementDesk rejectNone
Checklist contradicting the paperReview-stage damageOnly before the deadline
Theorem assumptions absent from the bodyReview-stage damageFixable in the writing pass

Final-week sequence for a theory-plus-experiments paper

  1. Freeze theorem statements and renumber assumptions; reviewers cross-reference labels.
  2. Regenerate every figure from seeded scripts so supplement and PDF cannot diverge.
  3. Fill the checklist against what the paper actually contains, not what is planned.
  4. Strip PDF metadata, notebook authorship fields, and repository owner strings.
  5. Confirm the OpenReview abstract matches the PDF abstract word for word.

Format anchors

  • AISTATS uses a two-column PMLR-style layout; display equations and algorithm blocks that fit a one-column draft routinely overflow, so compress math early rather than on deadline night.
  • The page counts cited above describe the 2026 cycle; treat every number as provisional and recheck the current Call for Papers before relying on it.

Output format

[AISTATS readiness] Ready / Needs fixes / Not ready
[Blocking checks] <OpenReview/page/anonymity/supplement/reproducibility/dual-submission>
[Statistical-evidence risk] <one issue>
[Desk-reject risk] <one issue>
[Fix order] <ordered fixes before submission>

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

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

brycewang-stanford의 스킬 모두 보기

이 스킬의 문제 신고