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.
日本語の概要は準備中です。原文の説明を表示しています。
Use when packaging ACM CCS artifacts for the artifact-evaluation committee and the ACM badges — Artifacts Available, Artifacts Evaluated Functional, Artifacts Evaluated Reusable, and Results Reproduced — covering what security evaluators inspect, how to make attacks and defenses turnkey, and how to justify withheld artifacts.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Use this for artifact packaging around CCS. CCS runs an optional artifact-evaluation process after acceptance; passing artifacts earn ACM badges that appear on the paper's first page. Reopen the current call for artifacts for the exact badge set, submission form, and deadlines.
| Badge | What it certifies | What the committee does |
|---|---|---|
| Artifacts Available | The artifact is publicly archived with a stable identifier | Confirms the artifact is retrievable and permanent |
| Artifacts Evaluated - Functional | The artifact runs and does what the paper says | Executes it against the documented steps |
| Artifacts Evaluated - Reusable | It exceeds functional quality and others can reuse it | Judges structure, documentation, and reusability |
| Results Reproduced | The main paper results are independently reproduced | Reruns experiments and checks they support the claims |
Available is about archival permanence; Functional and Reusable are about quality; Results Reproduced is the highest bar and requires the committee to regenerate your headline numbers.
| Claim type | First artifact inspected | Common failure caught |
|---|---|---|
| Exploit against real software | The PoC and its target build instructions | Target version unspecified; PoC fails to build |
| Defense with overhead numbers | The benchmark runner and instrumented build | Overhead cannot be reproduced; workload undocumented |
| Measurement study | The collection and classification scripts | Classification rule differs from the paper's prose |
| Cryptographic implementation | Test vectors and the reference build | No test vectors; outputs cannot be checked |
A hypothetical accepted paper presents a new fuzzer that found N bugs. For Reusable and Results Reproduced: ship a container pinning the fuzzer, the target corpus, and the seed set; document one command to reproduce a representative crash and one to rerun a bounded campaign; provide the bug list with disclosure status; and note which crashes are embargoed pending vendor patches, offering redacted reproducers for those.
[Target badges] available / functional / reusable / results-reproduced
[Contents] <code / data / container / test vectors / logs>
[Turnkey level] one-command / scripted / descriptive / weak
[Safe-handling] <gating and disclosure posture for dangerous artifacts>
[Withheld-and-justified] <what and why, with substitute offered>
[Fixes before submission] <ordered list>
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。