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Get Started Free →Use when auditing an AAAI main technical track submission for OpenReview readiness, double-blind anonymity, page limits, reproducibility checklist, supplementary material, author limits, multiple-submission policy, and AAAI AI-use policy compliance.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 32% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 35% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 83% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 34% | 0% |
| case-21 | ✗→✓ | ▲ Improved | -22% | 0% |
Use this for an AAAI main technical track submission audit. Reopen the current conference page, Author Kit, CFP, submission instructions, review process page, supplementary-material page, and author policies before giving deadline-ready advice.
Track-specific rules can differ.
metadata before the abstract and paper deadlines.
US Letter PDF, and 7 pages of technical content plus pages solely for references and the reproducibility checklist.
code/data, and metadata. Omit acknowledgments in the review version.
combined technical-track submissions and did not allow authors to be added after submission.
under review at another archival venue.
LLM-generated manuscript text, AI authorship, and AI-generated citations are policy risks.
AAAI's large reviewer pool and high volume mean a desk-level or Phase-1 cut is the most likely way to lose, so screen for the mechanical failures first.
| Check | Fast-fail trigger | Where it bites | | --- | --- | --- | | Page limit | technical content over the cap | desk return | | Anonymity | author name in PDF, code, or metadata | policy reject | | Checklist | missing or contradictory | Phase-1 distrust | | Dual submission | concurrent archival venue | ethics reject |
Build a single review-version packet before the abstract deadline, then refresh it before final submission. The packet is not a substitute for the official instructions; it is a way to make the submission audit reproducible and to keep late fixes from creating new policy problems.
| Packet item | What to capture | Failure it prevents | | --- | --- | --- | | Policy snapshot | current conference page, Author Kit, submission instructions, supplementary-material rules, and AI-use policy checked dates | applying stale AAAI-26 facts to a later cycle | | PDF proof | page count, paper size, style file, checklist placement, font/figure warnings, and metadata scrub result | desk return for formatting or anonymity | | Author ledger | OpenReview profiles, conflicts, subject areas, author-limit count, and author-list freeze status | profile conflict, over-limit author, late author change | | Supplement ledger | every appendix, multimedia, code/data ZIP, README, license note, and anonymous link policy decision | mutable web pointer or identity leak | | Ethics ledger | dual-submission status, human-subjects/data constraints, AI-use disclosure, plagiarism/citation check | policy reject after submission |
For each item, record the evidence path and the person who can fix it. If a rule is uncertain, mark it as "requires current chair/author-kit confirmation" instead of guessing.
Run anonymity checks in a fixed order so fixes do not reintroduce leaks:
self-citations.
required.
executable logs.
keywords.
The output should separate "must fix before submission" from "acceptable but document why." Do not rely on a single manual skim; use PDF metadata tools, archive listing, and text search when available.
A robotics-learning team has 7 strong technical pages but left an acknowledgments line and a GitHub URL with their lab name in the supplement. The audit flags anonymity as the highest summary-reject risk: the fix order is strip the acknowledgment, replace the link with an anonymous archive, scrub ZIP metadata, then re-export and re-run the anonymity sweep before the paper deadline.
text[AAAI readiness] Ready / Needs fixes / Not ready [Track] Main / AI for Social Impact / AI Alignment / other [Blocking checks] <page/anonymity/checklist/supplement/author-limit/dual-submission/AI-policy> [Highest summary-reject risk] <one issue> [Fix order] <ordered fixes before submission>
Other measured skills in the registry, with their headline benchmark lift.