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 ACM CCS paper for a precise threat model, calibrated attack/defense claims, 12-page ACM sigconf compression, double-blind wording, adaptive-evaluation honesty, and the security house style that survives an adversarial SIGSAC program committee.
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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. CCS papers must state who the attacker is, what the contribution defends or breaks, and enough measured evidence that an adversarial reviewer cannot poke the central claim.
| Draft pattern | CCS-safe rewrite |
|---|---|
| "Our attack is highly effective..." | "recovers the key in N queries against library X vY on platform Z" |
| "Under realistic assumptions..." | "Under threat model T (network MITM, no host access)..." |
| "Our defense is secure..." | "resists the adaptive attacker of Section 5 at C% overhead" |
| "We significantly reduce risk..." | Claim scoped to the deployment and versions measured |
A draft with a full protocol description, four attack variants, a formal proof, and six measurement figures: keep the threat model, the strongest attack variant end to end, one proof sketch, and the two decision-critical figures (leakage rate and defense overhead); push the other variants, the full proof, and raw measurement tables to appendices with forward references. The test of a good cut: a reviewer should be able to judge novelty and soundness of the attack without opening the appendix.
[Writing diagnosis] clear / under-specified threat model / overclaimed / overloaded
[First-page fix] <new framing>
[Claim discipline] <claim -> proof/measurement/exploit/cost>
[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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