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 preparing an accepted ACL main-conference or Findings paper for camera-ready, covering the extra content page, de-anonymization and acknowledgements, AI-assistance disclosure, keeping the Limitations section, ACL Anthology metadata and CC BY 4.0 publication, meta-review-driven edits, and presentation-mode logistics.
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 after ACL (or Findings of ACL) acceptance. Camera-ready quality controls how the paper looks forever in the ACL Anthology, which is the permanent open-access record. For ACL 2026 the camera-ready deadline was April 19, 2026 — confirm the current edition's date in the acceptance email before planning anything.
| Item | Why it matters at ACL | Common error |
|---|---|---|
| Title/abstract in the form | Becomes the Anthology landing page | Unicode or LaTeX macros pasted raw |
| Author names + order | Permanent citation record, BibTeX for everyone | Name spelled differently than prior papers |
| PDF fonts embedded | Anthology archival requirement | Missing Type-1/TrueType embedding from figures |
| License acceptance | Anthology publishes under CC BY 4.0 (post-2016 policy) | Assuming you can restrict reuse later |
| Video/poster uploads | Linked from the Anthology page when provided | Skipped, losing visibility |
Publication in the Anthology is open access with no author fee; ACL's cost model is conference registration, not APCs.
Work from the meta-review, not memory:
Day 1: meta-review edit checklist; claim-scope audit
Day 2: de-anonymize; acknowledgements incl. funding + AI disclosure
Day 3: public artifact links live; README + license on the repo
Day 4: rebuild with final style; font embedding + page-count check
Day 5: metadata form; abstract matches PDF; submit and archive everything
[Camera-ready status] Ready / Needs fixes / Blocked
[Meta-review edits] <requested change -> edit made>
[Extra-page budget] <what the added space was spent on>
[De-anonymization + disclosure] <authors/acks/AI-use/links status>
[Anthology package] <PDF/metadata/license/artifact links>
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。