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.
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Use this to prepare artifacts that reviewers can use to assess reproducibility. AAAI supplementary material is part of the submission record; after review starts, do not assume it can be updated.
AAAI does not run a separate badged artifact-evaluation committee the way some systems venues do; the same broad-AI reviewer who scores the paper also inspects whatever supplement you attach. That reviewer may be a planning, knowledge-representation, or constraint-satisfaction specialist rather than a deep-learning engineer, so the artifact has to be legible without insider tooling. Optimize for a reviewer who skims, not one who will spend an afternoon configuring a cluster.
| Reviewer action | Passes | Fails |
|---|---|---|
| Opens the ZIP | sane tree, top README | nested archives, 0-byte files |
| Reads appendix | maps to numbered claims | contradicts the paper |
| Tries one command | reproduces one headline number | needs private data or credentials |
| Scans for identity | nothing reveals authors | Git logs or home paths leak |
Because clearly-below-bar papers can be cut before author feedback, a supplement that looks thin or unrunnable is a cheap reason to summary-reject. Avoid these:
A constraint-solving paper claims a 30% node-expansion reduction. The team ships a large ZIP of raw
solver logs but no driver script. The reproduction path is empty, so artifact status is "risky"; the
fix is a small run_main.py that regenerates Table 2 from seeds, a trimmed log sample, and a license
for the benchmark instances. The raw dump moves to the post-acceptance release.
[Artifact status] complete / partial / risky / unavailable
[Submitted files] technical appendix / multimedia appendix / code-data ZIP
[Reviewer reproduction path] <commands and expected output>
[Anonymity risks] <metadata, links, paths, logs>
[Missing items] <data, code, seeds, licenses, hardware>
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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.
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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.
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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.
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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.
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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.
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Use when explaining or planning around AAAI's two-phase review process, Phase 1 rejection risk, Phase 2 additional reviews, AI-assisted review pilot, author feedback, SPC/AC discussion, and final decisions.
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