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acmmm-submission

Use when auditing an ACM MM (ACM Multimedia) submission for OpenReview readiness — thematic-area choice, the 6-8 page ACM sigconf budget, references-only overflow, double-blind anonymity versus the single-blind Reproducibility/Open-Source/Dataset tracks, supplementary media, dual submission, desk-re…

Install / Use

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-submission

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

85/100

Supported Platforms

Universal

Our assessment of acmmm-submission

acmmm-submission scores 85/100 on our quality scale, 2219th of 4,610 Development & Engineering skills we index (top 49%).

Its SKILL.md is 5.5 KB long, well organised into 9 sections with 1 code example: a solid amount of guidance for an agent.

With 1,158 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
17/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 18 days ago, so acmmm-submission is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

acmmm-submission compared with similar skills

All 4 of these similar skills score higher than acmmm-submission; compare them before choosing.

SkillScoreStarsUpdatedFormat
acmmm-submission (this skill)by brycewang-stanford851.2k18d agoSKILL.md
ai-job-searchby MadsLorentzen10044.8ktodayCLAUDE.md
claude-howtoby luongnv8910041.7k3d agoCLAUDE.md
algorithmic-artby anthropics100177.9k10d agoSKILL.md
pptxby anthropics100177.9k10d agoSKILL.md

Frequently asked questions

How do I install acmmm-submission?
Run npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acmmm-submission. The install tabs above show the steps for each supported agent.
Which AI agents does acmmm-submission work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is acmmm-submission safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is acmmm-submission still maintained?
The repository was last updated 18 days ago, so acmmm-submission is actively maintained.

name: acmmm-submission description: Use when auditing an ACM MM (ACM Multimedia) submission for OpenReview readiness — thematic-area choice, the 6-8 page ACM sigconf budget, references-only overflow, double-blind anonymity versus the single-blind Reproducibility/Open-Source/Dataset tracks, supplementary media, dual submission, desk-reject triggers, and last-week sequencing.

ACM MM Submission

Use this to run a pre-deadline audit of an ACM Multimedia paper. Reopen the current Call for Technical Papers, the Topics of Interest page, each relevant track call, and the OpenReview group before giving deadline-ready advice — ACM MM rewrites these each edition.

Submission audit

  • Confirm the target is the ACM MM main conference (or a specific track), not a co-located workshop, ACM MM Asia, MMSys, or ICMR.
  • Choose the thematic area deliberately: it routes the paper to a reviewer pool, and a mismatched area is a quiet source of off-topic reviews.
  • Apply the current ACM sigconf template with no margin, font, or spacing edits. ACM MM 2026 used a 6–8 page body; references may spill onto up to two additional pages that contain only references.
  • Enforce double-blind anonymity across the paper, appendix, supplement, code, media assets, filenames, PDF metadata, and repository links — unless submitting to the named single-blind tracks (Reproducibility, Open Source Software, Dataset), where the artifact's identity is expected.
  • Register the abstract before the abstract deadline; the paper and the supplement have their own later deadlines (in 2026: abstract Mar 25, paper Apr 1, supplement Apr 8, AoE).
  • Check concurrent-submission rules and prior-publication status; do not keep the same work under review at another archival venue when ACM MM forbids it.

Blocking risks

  • Late abstract registration or paper upload.
  • Overlength body or a tampered sigconf template.
  • Identity leak in the PDF, media metadata, demo watermark, or repository link (on a double-blind track).
  • Wrong track blinding — anonymizing a Dataset/Open-Source submission, or de-anonymizing a main-track one.
  • Non-rendering or proprietary-format supplementary media.
  • Dual submission to another archival venue.

Desk-reject and triage table

| Trigger | Severity at ACM MM | Repair window | |---|---|---| | Overlength body (past 8 pages) | Desk reject | None after the deadline | | Non-references content on the overflow pages | Desk reject or chair flag | Before the deadline only | | Author identity in a double-blind PDF/media | Desk reject | None | | Wrong thematic area | Off-topic reviews, not a desk reject | Fixable before the paper deadline | | Supplement that will not play for a reviewer | Lost evidence | Fixable before the supplement deadline | | Missing OpenReview coauthor profiles | Submission blocked | Before the deadline |

Last-week sequence for a cross-modal paper

  1. Freeze the thematic-area choice and confirm the paper's claims match that area's scope.
  2. Re-render every figure and media clip from scripts so body, supplement, and PDF agree.
  3. Anonymize media: strip author names from filenames, EXIF/metadata, and any on-screen watermark, and route dataset/demo links through an anonymous mirror.
  4. Confirm the OpenReview abstract matches the PDF abstract word for word.
  5. Verify the body fits 8 pages with the overflow pages holding references only.

OpenReview mechanics that trip people up

ACM MM runs on OpenReview, but the failure modes are administrative, not intellectual:

  • Every coauthor needs a complete OpenReview profile with a real institutional history, or the submission is blocked or the conflict graph is wrong.
  • The abstract is registered before the paper — a separate, earlier deadline. Missing it forecloses the paper deadline entirely.
  • Declare conflicts honestly; an undeclared conflict discovered later can sink a paper.
  • The thematic area is set at submission and is hard to change afterward; it selects your reviewers, so treat it as a first-class decision, not a dropdown afterthought.

Track and blinding double-check

The most ACM MM-specific desk-reject cause is submitting to the wrong track's blinding regime.

| If you are submitting to... | Blinding | So the PDF must... | |---|---|---| | Main track / Brave New Ideas | Double-blind | Hide all author identity, in text, media, and links | | Reproducibility track | Single-blind | Name the artifact and its authors as expected | | Open Source Software Competition | Single-blind | Present the real project and repository | | Dataset track | Single-blind | Identify the dataset and its providers |

Anonymizing a single-blind submission (or de-anonymizing a double-blind one) both signal that the authors did not read the track call — fix it before upload, not after.

Format anchors

  • ACM MM's two-column sigconf layout compresses hard: wide multimodal figures, algorithm blocks, and qualitative media grids overflow the 8-page body, so budget page space as a design decision early, not on deadline night.
  • The page counts, deadlines, and track blinding cited here describe the 2026 cycle; treat every number as provisional and recheck the current CFP and track calls before relying on it.

Output format

[ACM MM readiness] Ready / Needs fixes / Not ready
[Track + thematic area] <main/BNI/dataset/... + area>
[Blocking checks] <OpenReview/page/anonymity/media/dual-submission>
[Cross-modal evidence risk] <one issue>
[Desk-reject risk] <one issue>
[Fix order] <ordered fixes before submission>

Related Skills

View on GitHub
GitHub Stars1.2k
CategoryDevelopment
Updated18d ago
Forks153

Languages

Stata

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions