Skip to content
Content
Skill

/aistats-supplementary

Use when preparing AISTATS supplementary material, appendices, proof details, code/data archives, simulation scripts, additional tables, and anonymized artifacts under deadline, size, anonymity, and reviewer-discretion constraints, including how to split a

From plugin
awesome-journal-skills
965200 skills
Install
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill aistats-supplementary --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/aistats-supplementary

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use when preparing AISTATS supplementary material, appendices, proof details, code/data archives, simulation scripts, additional tables, and anonymized artifacts under deadline, size, anonymity, and reviewer-discretion constraints, including how to split a

SKILL.md

aistats-supplementary.SKILL.md
name: aistats-supplementary
description: Use when preparing AISTATS supplementary material, appendices, proof details, code/data archives, simulation scripts, additional tables, and anonymized artifacts under deadline, size, anonymity, and reviewer-discretion constraints, including how to split a theory-plus-experiments paper between body and supplement.

AISTATS Supplementary

Use this when assembling AISTATS supplementary material. The supplement can support the paper, but the main submission must remain understandable without it.

Supplement structure

  • Put theorem proofs, derivations, extra ablations, simulation details, dataset

documentation, and robustness tables in a clean appendix or supplementary manuscript.

  • Put executable assets in a separate archive when current OpenReview forms allow it.
  • Respect the current supplementary deadline. AISTATS 2026 placed supplementary-material

submission after the paper deadline but before review.

  • Keep all supplementary files double-blind: no authors, institutions, acknowledgements,

private paths, repository owners, grants, or identifying metadata.

  • Do not use the supplement to hide essential motivation, core method description, main

theorem statements, or primary empirical results.

  • Verify archives open on a clean machine and contain no credentials, cache directories,

large irrelevant files, or hidden OS metadata.

Appendix architecture for proofs

  • Order appendix sections to mirror main-text theorem order; statistician reviewers navigate

by theorem number, not by page.

  • Restate each theorem before its proof so the appendix reads standalone without flipping

back to the two-column body.

  • Standard partition: notation and assumptions, main proofs, auxiliary lemmas, additional

simulations, then real-data details.

  • Keep one proof-sketch paragraph per major theorem in the body itself; an AISTATS submission

whose entire argument lives in the supplement reads as unreviewable within the page limit.

  • Cross-reference every appendix table and lemma from the body at least once; orphaned

supplement material is invisible to reviewers and wasted under reviewer discretion.

  • If the cycle allows appendices inside the main PDF after the references, confirm against

the current instructions whether that or a separate file upload is expected.

What gets opened first

| Supplement item | Inspection likelihood | Practical implication | |---|---|---| | Proof of the headline theorem | High | Polish it to main-text standard | | Extra ablation and robustness tables | Medium | Reference each one from the body | | Code archive | Variable, reviewer discretion | The README must orient a reader in one minute | | Raw experiment logs | Low | Include for completeness, never rely on them |

Vignette: splitting an optimization paper

A submission proving a convergence guarantee for a stochastic mirror-descent variant, plus benchmark plots: the body keeps the theorem, the key lemma, the proof roadmap, and two decision-critical figures; the appendix holds full proofs and step-size sensitivity grids; the archive carries the seeded experiment runner. Nothing decision-critical lives only in the archive, because archive inspection at AISTATS is discretionary.

Output format

[Supplement status] Ready / Needs fixes / Not ready
[Files] <appendix/proofs/code/data/logs>
[Deadline] <current supplement deadline and source>
[Anonymity checks] <passed/issues>
[Main-paper dependency] <what breaks if supplement is ignored>
Read more
Ships withawesome-journal-skills

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

Get the whole plugin
Stats
965
Stars
121
Forks
Active
Maintenance
Stata
Language
MIT
License
13h ago
Last commit
2mo ago
Created

Repo: brycewang-stanford/Awesome-Journal-Skills

Other skills on awesome-journal-skills.