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 when revising an AISTATS paper for concise AI-statistics framing, theorem-and-experiment clarity, 8-page two-column compression, double-blind wording, reproducibility clarity, statistically careful claims, and assumption-labeling discipline that survives statistician reviewers.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Use this when revising the main paper. AISTATS papers need compact statements of why a statistical or ML contribution matters and enough detail for technical validation.
| Draft pattern | AISTATS-safe rewrite |
|---|---|
| "Our method significantly outperforms..." | "reduces mean error by X (SE Y) over Z seeded runs" |
| "Under mild conditions..." | "Under Assumptions 1-3 (boundedness, ...)" |
| "It is easy to see that..." | "By Lemma 2 and the triangle inequality..." |
| "Achieves state-of-the-art..." | Claim scoped to the regimes actually tested |
A draft with three theorems, six figures, and a sprawling related-work section: keep all theorem statements, one sketch each, and the two decision-critical figures (the rate plot and the coverage plot); compress related work into contribution contrasts; move secondary lemmas and four figures to the appendix with explicit forward references. The test of a good cut: a reviewer should reconstruct the whole argument without ever opening the supplement.
[Writing diagnosis] clear / under-justified / overclaimed / overloaded
[First-page fix] <new framing>
[Claim discipline] <claim -> proof/experiment/limitation>
[Compression cuts] <move/delete/merge>
[Anonymity edits] <phrases to rewrite>
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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 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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