本文へ移動
cccskills
無料GitHub で公開

acmmm-supplementary

Use when organizing the ACM MM (ACM Multimedia) supplementary material due after the paper deadline — deciding what belongs in the 6-8 page body versus the supplement, packaging video/audio/interactive demos that render on a reviewer's machine, keeping all assets anonymous for double-blind tracks, and pointing to code and data.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

ACM MM Supplementary Material

Use this to plan the ACM Multimedia supplement, which has its own deadline after the paper (in 2026, April 8 versus the April 1 paper deadline). For a multimedia paper the supplement is not an afterthought — it is where the video, audio, and interactive evidence lives.

Body vs. supplement split

The 6–8 page sigconf body carries the argument; the supplement carries what the argument rests on but cannot fit.

ContentBodySupplement
Core claim, main results table, teaserYes—
The two or three decisive media examplesYes (stills/short)Full clips
Extra qualitative media across conditions—Yes
Full user-study protocol and per-rater dataSummary onlyYes
Hyperparameters, extra ablations, proofsPointer onlyYes
Code / data pointersNamedYes

A reviewer must be able to follow the body without the supplement; the supplement then confirms rather than completes the argument.

Packaging media that actually plays

The single most common ACM MM supplement failure is media a reviewer cannot open.

video:  H.264/MP4, standard resolution, plays in a browser/VLC; no exotic codec
audio:  WAV or MP3; label each clip with the claim it supports
demo:   if interactive, provide a recorded fallback video — do not assume the reviewer runs it
size:   keep within the cycle's stated limit; compress rather than omit evidence
index:  a short README mapping each file to the paper claim/figure it supports

Anonymity for double-blind tracks

  • Strip author names from filenames, EXIF/media metadata, and any on-screen watermark or slate.
  • Remove identifying voices/faces of the authors from demo videos where they would reveal identity, or note that they are incidental.
  • Route dataset and code links through an anonymous mirror; a personal or lab URL is a leak.
  • The Reproducibility, Open Source Software, and Dataset tracks are single-blind and do not need this — but the main track and Brave New Ideas do.

Make the supplement legible

  • Open with a one-paragraph README: what is here, and which paper claim each file supports.
  • Order files to follow the paper's sections, not upload order.
  • Caption every clip; an unlabeled video is not evidence a reviewer can use.

What reviewers actually open

Reviewers are time-pressed and will not download a 2 GB archive or install a codec. Design for a skim:

  • Lead the index with the two or three clips that decide the paper, labeled by claim.
  • Keep individual files small enough to stream; compress rather than omit.
  • Never make the argument depend on a file the reviewer has to run or build — provide a recorded fallback for any interactive demo.

Format and codec table

AssetSafe choiceAvoid
VideoH.264/MP4, standard resolutionExotic/proprietary codecs, 4K walls of clips
AudioWAV or MP3, labeledUnlabeled waveforms, lossless dumps for size's sake
Interactive demoRecorded MP4 fallback + optional codeAssuming the reviewer runs your app
AppendixPDF, same template familyA zip of loose screenshots

Timing against the paper deadline

The supplement has its own, later deadline (April 8 vs. April 1 in 2026), which is a chance and a trap: do not defer all media to that week, because rendering, compressing, and anonymizing a video library takes longer than expected. Freeze the decisive clips with the paper, and use the extra days for the confirmatory extras, not the core evidence.

Pre-submission checklist

  • Every media file opens with common open-source players.
  • The index maps each file to a specific figure, table, or claim.
  • No author identity in any filename, metadata, watermark, or link (double-blind tracks).
  • The body still stands alone if the supplement were removed.
  • Total size is within the current cycle's stated cap (待核实 each year).

Output format

[Split] body self-contained / body depends on supplement
[Media playability] all files open / risky: <list>
[Anonymity] clean / leaks: <list>
[Index] each file mapped to a claim / unlabeled: <list>
[Size] within cap / over
[Top fixes] <ordered before the supplement deadline>

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

brycewang-stanford のスキルをすべて見る

このスキルの問題を報告する