brycewang-stanford/awesome-journal-skills/aistats-workflow

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Use when planning an AISTATS project timeline from venue fit through abstract submission, full-paper upload, supplementary material, review release, author-reviewer discussion, decision, camera-ready, PMLR publication, registration, presentation, and artifact release, with backward-planning offsets for theory-plus-experiments papers.

Install

npx vskill@latest install brycewang-stanford/awesome-journal-skills/aistats-workflow

SKILL.md

AISTATS Workflow

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

AISTATS 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 General Chairs and Program Chairs (2026 General Chairs: Emtiyaz Khan and Yingzhen Li; Program Chairs: Arno Solin and Aaditya Ramdas, verified 2026-06-22), and the cost model is registration fees, not APCs — PMLR proceedings are open-access with no author fee. Conference organizers rotate yearly, so re-check the current CFP and organization page rather than carrying a name forward.

Milestones

  • Venue fit: confirm the contribution is genuinely at the AI, ML, and statistics interface.
  • Evidence lock: freeze theorem statements, assumptions, experiments, simulations,

baselines, reproducibility checklist, and supplement contents.

  • Abstract deadline: submit real title, abstract, authors, subject areas, and conflicts.
  • Full-paper deadline: upload anonymous PDF and required OpenReview fields.
  • Supplement deadline: upload anonymized appendix/code/data if current cycle allows or

requires separate supplementary material.

  • Review release: triage correctness, statistical validity, novelty, clarity, and

reproducibility concerns.

  • Discussion period: draft concise anonymous text-only clarifications; avoid forbidden links

or unsupported new results.

  • Decision: archive reviews, discussion, meta-review, decision, and submitted versions.
  • Acceptance: prepare PMLR camera-ready files, registration, in-person presentation, and

public artifact release.

Backward plan from the paper deadline

Weeks out (heuristic)Theory-plus-experiments milestone
8+Theorems proved, assumption set frozen
6Simulations designed against each theorem
4Real-data runs complete, seeds logged
3Full draft sitting in AISTATS two-column format
2Internal mock review by a statistics-minded reader
1Checklist pass, anonymity sweep, supplement assembly
0Abstract then full paper on OpenReview; supplement by its own cutoff

These offsets are planning heuristics only — anchor every one of them to the current official timetable, never to a previous cycle's calendar.

Failure modes by stage

  • Theory still moving at week 3 forces last-minute theorem edits nobody has verified — the

classic AISTATS correctness reject in the making.

  • Leaving format conversion to the final week surfaces overflow late, because two-column math

is far tighter than a one-column working draft.

  • Skipping the mock review forfeits the only chance to hear "your experiments violate

Assumption 2" from a friend instead of a reviewer.

  • Building the supplement after the paper deadline under time pressure is how anonymity

leaks ship.

Coordination notes

  • Assign one named owner for the reproducibility checklist and another for the anonymity

sweep; shared ownership is how both slip.

  • Archive the exact submitted PDF, supplement, and checklist, since discussion-phase replies

must quote them precisely.

Output format

text
[Current stage] idea / experiments / writing / abstract / submission / supplement / discussion / accepted
[Next official deadline] <date and source, or unknown>
[Critical path] <three tasks that determine readiness>
[Risk register] <page/anonymity/statistical evidence/supplement/reproducibility/presentation>
[Owner map] <task -> person or role>

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

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