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 ACL author response inside an ACL Rolling Review cycle on OpenReview, covering the response window before meta-review, reviewer discussion dynamics, score-change strategy, flagging review issues to the area chair, anonymity rules, and deciding between responding now versus revising for a later ARR cycle.
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 when ARR reviews land. The response is written inside the review cycle, before the meta-review is finalized — its primary reader is the area chair who will summarize your paper for whatever conference you later commit to. Reopen aclrollingreview.org/reviewing for the current cycle's exact window and rules.
| Objection | Underlying worry | Response that works at ACL |
|---|---|---|
| "Only evaluated on English" | Overclaimed generality | Scope the claim explicitly; cite the multilingual appendix run if one exists |
| "Gains may be contamination" | Test data in pretraining | Point to the decontamination check or concede and describe the planned audit |
| "No error analysis" | Numbers without understanding | Quote the analysis section or summarize 2-3 systematic error classes from logged outputs |
| "Human eval lacks agreement stats" | Unreliable judgments | Report the IAA already computed; never invent a number in the response box |
| "Missing recent baseline X" | Stale comparison set | Distinguish X technically, or accept it as revision work with a stated plan |
We thank Reviewer X. Main point first: [one-sentence resolution].
1. [Factual correction] The model is trained only on the training split
(Section 3.2, line refs); Table 2 reports held-out results.
2. [Clarification] The claim is scoped to the five languages tested
(Section 5); we will tighten the abstract wording.
3. [Evidence pointer] Seeds, prompts, and compute are in Appendix C and
checklist items C1-C3.
4. [Deferred work] A comparison to X requires retraining; we commit to it
in a revision and note why it should not change the ranking.
[Response stance] clarify-in-cycle / concede-and-revise / mixed
[Meta-review target] <sentence you want the AC to write>
[Per-reviewer plan] <R1/R2/R3: main point + evidence anchor>
[Review-issue flags] <deficient-review reports to AC, if any>
[Deferred to resubmission] <experiments promised for a later cycle>
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。