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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when an Advanced Materials manuscript must be fit to its article-type format — Communication versus Research Article — where word count and display items are budgeted together against a typeset page limit. Manages the length budget; does not restructure the science or polish prose line by line.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Advanced Materials counts length in typeset published pages, not manuscript pages — a double-spaced 25-page manuscript may typeset to far fewer pages in the two-column layout. Word count and display items (figures, schemes, tables) count together against the page budget. Approximate targets (verify current limits on the author page):
| Article type | Typeset budget (approx.) | Abstract | Display items (approx.) |
|---|---|---|---|
| Communication | ~4 published pages (~3500 words) | none — opening paragraph acts as abstract | ~4 figures/tables |
| Research Article | ~10 published pages (~3000–8000 words) | short abstract (~200 words) + 3–7 keywords | ~3–8 display items |
| Review / Progress | longer, by invitation/agreement | structured per type | many |
A large or multi-panel figure consumes a disproportionate slice of the page budget: adding a panel can cost a paragraph of text.
Trim only after the central advance, characterization, and figures are stable, so you cut padding, not evidence:
advmat-writing-style).advmat-supplementary).Never trim: the decisive characterization, the benchmarking, or the headline metric's statistics.
【Article type】Communication / Research Article — matches content? yes / reconsider
【Typeset page estimate】within budget? yes / over by ~X
【Display items】counted with text? N figures + M tables
【Trim done】hype / prose / secondary-data-to-SI / figures / refs
【Untouched】characterization + benchmarking + statistics intact? yes
【Next】advmat-cover-letter or advmat-submission
Page limits, word counts, abstract/keyword rules, and display-item allowances differ by article type and change — verify all on the official Wiley Advanced Materials author page.
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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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.