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-submissionInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
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.
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.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| acmmm-submission (this skill)by brycewang-stanford | 85 | 1.2k | 18d ago | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 44.8k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 3d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 10d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 10d ago | SKILL.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.
Skill content
View source on GitHubname: 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
sigconftemplate 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
- Freeze the thematic-area choice and confirm the paper's claims match that area's scope.
- Re-render every figure and media clip from scripts so body, supplement, and PDF agree.
- Anonymize media: strip author names from filenames, EXIF/metadata, and any on-screen watermark, and route dataset/demo links through an anonymous mirror.
- Confirm the OpenReview abstract matches the PDF abstract word for word.
- 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>
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
