aaai-artifact-evaluati…
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance…
Use when preparing the ACM MM (ACM Multimedia) camera-ready version of record — de-anonymizing safely, completing the ACM rights form and CCS concepts, meeting ACM sigconf requirements, releasing code/data/media artifacts and any earned reproducibility badge, registering, and
Claude Code
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready --agent claude-code
Codex
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready -a codex -y
Cursor
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready -a cursor -y
Gemini CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready -a gemini-cli -y
GitHub Copilot
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready -a github-copilot -y
OpenCode
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready -a opencode -y
Windsurf
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-camera-ready -a windsurf -y
name: acmmm-camera-ready description: Use when preparing the ACM MM (ACM Multimedia) camera-ready version of record — de-anonymizing safely, completing the ACM rights form and CCS concepts, meeting ACM sigconf requirements, releasing code/data/media artifacts and any earned reproducibility badge, registering, and planning the oral/poster presentation in Rio.
Use this after acceptance to turn the reviewed PDF into the ACM Digital Library version of record. Camera-ready is a distinct piece of work with its own deadline (reported August 6 for 2026) and its own failure modes — several of them ACM-specific.
The reviewed paper was anonymous (main track); the camera-ready is not. Reverse the blinding carefully:
| Item | What to do | |---|---| | ACM rights form | Complete the eRights process; paste the returned rights block and DOI into the paper | | CCS concepts | Add ACM Computing Classification System concepts and author keywords | | sigconf compliance | Final PDF in the current ACM `sigconf` template; pass ACM's PDF/format check | | Reference/overflow | References may occupy the extra pages; the body stays within the accepted length | | Metadata | Title, authors, affiliations, and abstract match the ACM submission exactly |
The exact ACM rights/OA options (including ACM Open) are settled here; confirm the current process (待核实 each cycle).
code: public repo + archived DOI, LICENSE, README with run instructions data: dataset card, license, access path (mirror or agreement) media: final demo video/audio, now de-anonymized, playable in open players badge: if the Reproducibility track awarded a badge, include the badge and artifact link
Camera-ready is when the public release replaces the anonymous review artifact — do not leave the community pointing at a dead anonymous link.
registration category and any presenter requirement.
logistical failure.
audience should see/hear the seam your paper exploits.
media example; bring a device to play a short clip.
1. Receive the ACM eRights email after acceptance; complete the rights/permissions form. 2. ACM returns the rights block + DOI + the correct conference string. 3. Paste that block verbatim into the sigconf template (do not hand-edit it). 4. Add CCS concepts and keywords; run ACM's PDF format/preflight check. 5. Upload the final PDF and source where required, matching the registered metadata.
Skipping or mistyping the rights block is a frequent camera-ready bounce; treat the returned text as fixed data, not prose to reword.
versions in the accepted formats, captioned and playable in open players.
anonymous review mirror.
[De-anonymization] complete / residual anonymous text: <list> [ACM publishing] rights + CCS + sigconf done / gaps: <list> [Artifact release] public + archived / gaps [Registration] done / pending [Presentation] oral/poster plan ready / to do [Blocking items] <ordered before the camera-ready deadline>
Stanford REAP × CoPaper.AI · 由斯坦福实证方法论团队精选与维护 访问 copaper.ai 微信:CoPaper.AI 按 11 个主流学科板块覆盖 经管与商科 社会科学 人文学科 数学与物理科学 生命科学 医学与健康 工程与技术 计算机科学与 AI 体育科学 点击任一学科名可跳转到对应说明;每类下的代表子领域在正文总览中完整列出。下方封面墙按 venue 导航,完整分类见覆盖一览。 🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🧪 自动实证
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