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Acmmm Camera Ready

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brycewang-stanford
acmmm-camera-ready

Use when preparing the ACM MM (ACM Multimedia) camera-ready version of record — de-anonymizing safely, completing the ACM rights form and CCS concepts, meeting ACM sigconf requirements, releasing code/data/media artifacts and any earned reproducibility badge, registering, and planning the oral/poster presentation in Rio.

Overview

Publisherbrycewang-stanford
RepositoryAwesome-Journal-Skills
Skill nameacmmm-camera-ready
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 Acmmm Camera Ready 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/ACM-MM-Skills/skills/acmmm-camera-ready
  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/ACM-MM-Skills/skills/acmmm-camera-ready .claude/skills/acmmm-camera-ready
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Acmmm Camera Ready 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 Acmmm Camera Ready 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 Acmmm Camera Ready 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.

ACM MM Camera-Ready

Use this after acceptance to turn the reviewed PDF into the ACM Digital Library version of record. Camera-ready is a distinct piece of work with its own deadline (reported August 6 for 2026) and its own failure modes — several of them ACM-specific.

De-anonymization pass

The reviewed paper was anonymous (main track); the camera-ready is not. Reverse the blinding carefully:

  • Add author names, affiliations, and acknowledgements/funding.
  • Restore "our previous work" phrasing and the real repository/dataset URLs.
  • Replace the anonymous data/code mirror with the permanent, public archive (DOI).
  • Re-check that no anonymous-only placeholder text survives.

ACM publishing requirements

ItemWhat to do
ACM rights formComplete the eRights process; paste the returned rights block and DOI into the paper
CCS conceptsAdd ACM Computing Classification System concepts and author keywords
sigconf complianceFinal PDF in the current ACM sigconf template; pass ACM's PDF/format check
Reference/overflowReferences may occupy the extra pages; the body stays within the accepted length
MetadataTitle, authors, affiliations, and abstract match the ACM submission exactly

The exact ACM rights/OA options (including ACM Open) are settled here; confirm the current process (待核实 each cycle).

Artifact and badge release

text
code:    public repo + archived DOI, LICENSE, README with run instructions
data:    dataset card, license, access path (mirror or agreement)
media:   final demo video/audio, now de-anonymized, playable in open players
badge:   if the Reproducibility track awarded a badge, include the badge and artifact link

Camera-ready is when the public release replaces the anonymous review artifact — do not leave the community pointing at a dead anonymous link.

Registration and attendance

  • At least one author must register by the deadline and present; confirm the current registration category and any presenter requirement.
  • Check visa/travel needs for Rio de Janeiro early — international travel is the common logistical failure.

Presentation prep by tier

  • Oral: a talk that leads with the cross-modal contribution and plays the media — the audience should see/hear the seam your paper exploits.
  • Poster: a single readable visual with the teaser, the mechanism, and one decisive media example; bring a device to play a short clip.
  • Prepare captioned media that works offline; conference A/V and network are unreliable.

The ACM eRights step, in order

text
1. Receive the ACM eRights email after acceptance; complete the rights/permissions form.
2. ACM returns the rights block + DOI + the correct conference string.
3. Paste that block verbatim into the sigconf template (do not hand-edit it).
4. Add CCS concepts and keywords; run ACM's PDF format/preflight check.
5. Upload the final PDF and source where required, matching the registered metadata.

Skipping or mistyping the rights block is a frequent camera-ready bounce; treat the returned text as fixed data, not prose to reword.

Media for the ACM Digital Library

  • Supplementary video/audio can accompany the DL record; provide the de-anonymized final versions in the accepted formats, captioned and playable in open players.
  • Ensure the public artifact link in the paper resolves to the permanent archive, not the old anonymous review mirror.
  • If a badge was awarded, include the ACM badge and the artifact DOI so the DL entry carries it.

Final camera-ready checklist

  • De-anonymized fully; rights block and DOI in place; CCS concepts added.
  • sigconf format check passed; metadata matches ACM record.
  • Public artifact archived and linked; any badge included.
  • Registration done; presentation media prepared and offline-safe.

Output format

text
[De-anonymization] complete / residual anonymous text: <list>
[ACM publishing] rights + CCS + sigconf done / gaps: <list>
[Artifact release] public + archived / gaps
[Registration] done / pending
[Presentation] oral/poster plan ready / to do
[Blocking items] <ordered before the camera-ready deadline>

Frequently asked questions

What does the Acmmm Camera Ready AI skill do?

Use when preparing the ACM MM (ACM Multimedia) camera-ready version of record — de-anonymizing safely, completing the ACM rights form and CCS concepts, meeting ACM sigconf requirements, releasing code/data/media artifacts and any earned reproducibility badge, registering, and planning the oral/poster presentation in Rio.

Why use Acmmm Camera Ready on TypingMind?

Because you install it once and use it with any model. Acmmm Camera Ready 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 Acmmm Camera Ready in TypingMind?

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

Which AI models can use Acmmm Camera Ready?

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 Acmmm Camera Ready?

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

Is the Acmmm Camera Ready 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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