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Acl Submission

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brycewang-stanford
acl-submission

Use when auditing an ACL submission before an ACL Rolling Review cycle deadline, covering long/short paper page budgets, the mandatory Limitations section, Responsible NLP checklist, anonymized PDFs and supplements, preprint declarations, dual-submission rules, resubmission linking, and ARR desk-reject triggers on OpenReview.

Overview

Publisherbrycewang-stanford
RepositoryAwesome-Journal-Skills
Skill nameacl-submission
Stars
1.2K
Forks
159
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by brycewang-stanford on GitHub. Read the source before you install it.

Installation

Install the Acl Submission AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACL-Skills/skills/acl-submission
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git /tmp/Awesome-Journal-Skills
mkdir -p .claude/skills
cp -r /tmp/Awesome-Journal-Skills/ACL-Skills/skills/acl-submission .claude/skills/acl-submission
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Acl Submission in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Acl Submission on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Acl Submission is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ACL Submission

Run this audit before uploading to an ACL Rolling Review (ARR) cycle on OpenReview. ACL papers are not submitted to the conference directly: they enter an ARR cycle, collect reviews and a meta-review, and are later committed to ACL. Reopen the current ARR CFP at aclrollingreview.org/cfp and the target conference's call before trusting any number below.

Two-step reality check

  • Confirm which ARR cycles feed your target ACL edition. ACL 2026 accepted work from the October 2025 and January 2026 cycles; committing requires a complete review package, so the last eligible cycle is earlier than the conference date suggests.
  • The ARR deadline is the hard one. Commitment is a separate, later form with its own deadline (March 14, 2026 for ACL 2026) — see acl-workflow for the calendar.
  • All ARR deadlines run 11:59 pm UTC-12 (anywhere on Earth).

Format gate

  • Long papers: up to 8 content pages. Short papers: up to 4. Both get unlimited pages for references, plus unlimited space after the conclusion for the required Limitations section and an optional ethics statement.
  • A missing Limitations section or overlength content is an explicit desk-reject condition under the ARR CFP — this is the most common self-inflicted rejection.
  • Use the official ACL LaTeX/Word style files unmodified; margin, font, or spacing tampering is treated as a length violation.
  • Appendices go after references in the same PDF; reviewers are not obliged to read them, so the 8 or 4 content pages must carry the whole argument.

Anonymity gate

  • The submission itself must be fully anonymized: no names, affiliations, acknowledgements, or self-revealing "we previously showed" citations.
  • Since January 2024 there is no anonymity period: you may post a non-anonymous preprint at any time. But you must declare preprint status at submission, and choosing "no non-anonymous preprint" earns award eligibility and priority for borderline decisions — then posting one anyway before meta-review release is a desk-reject offense.
  • Supplementary archives, repo links, and dataset pages must be anonymized too; links to tracked hosting (personal Dropbox/Drive) are disallowed.

Declarations that gate the submission form

Form itemWhat ARR checksFailure mode
Responsible NLP checklistCompleted, consistent with the PDFMisleading answers → desk reject
Resubmission linkPrior ARR submission ID + change summaryUnacknowledged resubmission → desk reject
Preprint declarationMatches what is actually on arXivBroken "no preprint" pledge → desk reject
Dual submissionNot under review anywhere archivalViolation → reject at ARR or venue
AI assistance disclosureChecklist item E answered honestlyUndisclosed generative-AI use → policy breach

Resubmission discipline

ARR is built for revise-and-resubmit across cycles. If this paper was reviewed in an earlier cycle:

  1. Link the previous submission ID in the form — omitting it is desk-rejectable.
  2. Attach a summary of changes plus a point-by-point response to every weakness named in the old reviews.
  3. If the previous meta-review scored 1, a resubmission within six months without wholesale revision can be desk rejected; cosmetic edits waste a cycle.
  4. Decide whether to request the same reviewers — continuity helps when the revision genuinely answers them.

Final-72-hours sequence for an NLP paper

  1. Rebuild the PDF from the untouched style files and re-run the page count on content pages only.
  2. Re-read Limitations: it must be substantive (scope, languages, data, compute), not a ritual paragraph.
  3. Fill the Responsible NLP checklist against the actual PDF — every "yes" needs a section number.
  4. Sweep the supplement archive for author names in paths, notebook metadata, git history, and license headers.
  5. Verify title/abstract on OpenReview match the PDF, and the preprint declaration matches arXiv reality.
  6. Submit hours early; ARR deadlines are AoE but OpenReview outages are not an accepted excuse.

Cycle-choice quick checks

  • Is the target conference actually accepting commitments from this cycle? Each edition names its eligible cycles; a mismatch strands the reviews.
  • Does the team have bandwidth during this cycle's author-response window, roughly five weeks after the deadline?
  • Would waiting one cycle allow the missing experiment that reviews will otherwise demand? A weak first cycle costs more than it saves, because the package follows the paper.
  • Is any co-author's other submission in the same cycle a conflict for reviewer assignment? Register conflicts and profiles before deadline week.

Frequently mishandled cases

  • Short paper padded to eight pages: reviewers rate contribution against format; a four-page idea submitted long scores as thin, not as generous.
  • Appendix used as overflow body: content pages must carry the argument; a method section that says "see Appendix B" for its core mechanism fails the self-containedness expectation.
  • arXiv v2 posted mid-cycle after declaring no preprint: this converts a declaration into a desk-reject liability — update plans, not the preprint.
  • Dataset "available on request": allowed, but checklist answers must then explain reproduction honestly rather than implying release.
  • Same work at a non-archival workshop: usually permitted, but most *ACL workshop proceedings ARE archival — verify the workshop's archival status in writing before assuming.

Output format

text
[ARR readiness] Ready / Needs fixes / Not ready
[Cycle + venue plan] <ARR cycle -> intended commitment venue>
[Format gate] <length/Limitations/style-file findings>
[Anonymity + declarations] <checklist/preprint/resubmission/dual-submission findings>
[Desk-reject risks] <ranked list>
[Fix order] <what to change before the cycle deadline>

Frequently asked questions

What does the Acl Submission AI skill do?

Use when auditing an ACL submission before an ACL Rolling Review cycle deadline, covering long/short paper page budgets, the mandatory Limitations section, Responsible NLP checklist, anonymized PDFs and supplements, preprint declarations, dual-submission rules, resubmission linking, and ARR desk-reject triggers on OpenReview.

Why use Acl Submission on TypingMind?

Because you install it once and use it with any model. Acl Submission is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Acl Submission in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ACL-Skills/skills/acl-submission. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Acl Submission?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Acl Submission?

As many as you like. As long as a model supports skills, you can use Acl Submission with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Acl Submission AI skill free?

Yes. It is published on GitHub by brycewang-stanford under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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