跳到正文
cccskills
免费在 GitHub 公开

aistats-author-response

Use when drafting AISTATS author responses or author-reviewer discussion replies under OpenReview, covering text-only discussion, no-link guidance, no revised-paper upload, anonymity requirements, statistician-reviewer pushback patterns, and decision-focused clarification strategy for theory-plus-experiments papers.

中文简介正在准备中。当前显示原文说明。

实测评分 未实测

查看安装方法

包含的文件(1)

  • SKILL.md3.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

AISTATS Author Response

Use this after AISTATS reviews are released. Reopen the current OpenReview instructions and author-discussion policy before drafting because response mechanics are cycle-specific.

Triage

  • Answer concerns that affect correctness, novelty, statistical validity, clarity, reproducibility, or fit for AISTATS.
  • Use existing submitted evidence: paper sections, appendices, supplementary material, theorem statements, experiments, checklist entries, and code/data descriptions.
  • Keep the reply anonymous. Do not reveal institution, authorship, grants, private URLs, or repository ownership.
  • Treat discussion as clarification, not revision. Do not depend on uploading a revised paper or new supplement unless current instructions explicitly allow it.
  • If current rules prohibit links, do not use URLs in the discussion. AISTATS 2026 author-reviewer discussion was text-only and links were not allowed.
  • Correct factual errors first, then address requests for missing comparisons, uncertainty estimates, proofs, or hyperparameters.

Drafting pattern

  1. State the decision-critical correction or concession.
  2. Point to exact submitted evidence.
  3. Explain the statistical or theoretical consequence.
  4. Promise a camera-ready wording fix only if it does not add unsupported new claims.

Statistician-reviewer pushback patterns

PushbackWhat it signalsAISTATS-ready fix
"Assumption A3 seems strong"The reviewer traced the proof chainPoint to where A3 is verified, weakened, or shown necessary; never dismiss it as standard without a citation
"The experiments violate the theorem conditions"Theory-experiment mismatch spottedIdentify which conclusions survive misspecification and cite the robustness simulation that shows it
"Observed rates do not match the bound"The reviewer compared empirical slopes against theoryReference the log-log plot, or explain the constant-dominated regime at the tested sample sizes
"Comparison with the classical statistical method is missing"Statistics-literature gapAnchor to the appendix comparison, or concede and scope a camera-ready clarification

Response micro-example

Reviewer objection: the minimax claim hides its dependence on dimension d. Reply skeleton:

  1. Concede that the d-dependence appears only in the appendix constant.
  2. Quote the exact constant from Theorem 2 so the reviewer need not search.
  3. Note that the simulation at d = 100 in Figure 4 follows the predicted scaling.
  4. Offer one camera-ready sentence making the dependence explicit in the main text.

Discussion-phase calibration

  • One decision-critical point per reviewer beats exhaustive replies; AISTATS meta-reviewers read for whether the central statistical objection was actually resolved.
  • Never paste new theorem statements or fresh proofs into the discussion box; sketch the argument and anchor it in submitted material only.
  • Respond early in the window — AISTATS discussion periods are short and reviewers who reply once rarely reply twice.
  • Length and formatting norms vary by cycle; recheck the current discussion instructions before sending anything.

Output format

[Priority issue] <reviewer concern>
[Decision dimension] correctness / novelty / statistical validity / clarity / reproducibility
[Draft response] <AISTATS-ready anonymous text>
[Evidence anchor] <paper/appendix/supplement item>
[Forbidden content removed] <links, identity leaks, new unsupported claims>

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

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.

中文简介正在准备中。当前显示原文说明。

brycewang-stanford/Awesome-Journal-Skills13002026年9月27日 更新

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.

中文简介正在准备中。当前显示原文说明。

brycewang-stanford/Awesome-Journal-Skills13002026年9月27日 更新

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.

中文简介正在准备中。当前显示原文说明。

brycewang-stanford/Awesome-Journal-Skills13002026年9月27日 更新

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.

中文简介正在准备中。当前显示原文说明。

brycewang-stanford/Awesome-Journal-Skills13002026年9月27日 更新

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.

中文简介正在准备中。当前显示原文说明。

brycewang-stanford/Awesome-Journal-Skills13002026年9月27日 更新

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.

中文简介正在准备中。当前显示原文说明。

brycewang-stanford/Awesome-Journal-Skills13002026年9月27日 更新

查看 brycewang-stanford 的全部技能

报告此技能的问题