icml-related-work
GitHub针对ICML投稿，分析相关工作以应对新颖性争议和并发提交风险。覆盖邻近会议文献、匿名引用重叠作者工作，提供差异化陈述模板及审稿意见修复策略，输出风险评估与重写建议。
触发场景
安装
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icml-related-work -g -y
SKILL.md
Frontmatter
{
"name": "icml-related-work",
"description": "Use when positioning an ICML submission against close ML literature, concurrent ICML submissions, recent public papers, workshop papers, ICLR\/AISTATS\/NeurIPS neighbors, and prior work under double-blind constraints."
}
ICML Related Work
Use this when novelty, incremental contribution, or concurrent-submission handling is the risk. ICML 2026 treats related concurrent ICML submissions with overlapping authors as prior work.
Required coverage
- Closest ML methods, theory, datasets, benchmarks, and evaluation papers.
- Neighboring venue papers from NeurIPS, ICLR, AISTATS, UAI, COLT, MLSys, KDD, ACL, CVPR, and other relevant areas.
- Related concurrent ICML submissions by overlapping authors; cite anonymously and include PDFs in supplementary material when a reasonable reviewer would expect them.
- Workshop papers without published proceedings generally do not trigger dual-submission violation, but their relationship still needs honest positioning.
- Very recent public work close to the full-paper deadline can be treated as concurrent, but good judgment and subfield norms matter.
Delta paragraph
<Prior work> addresses <problem> using <mechanism>. It leaves <specific gap>.
Our submission differs by <technical delta>, and this matters because <evidence>.
Novelty-pushback table (ICML reviewer reflexes)
ICML reviewers triage novelty fast because the load is heavy and the first PMLR page must already signal the delta. Map the likely objection to a venue-specific repair.
| Reviewer objection | What it means at ICML | Repair before submission |
|---|---|---|
| "This is a known trick rebranded" | Mechanism overlaps a COLT/NeurIPS result | Cite it, state the assumption or rate that differs, move the delta to page 1 |
| "Concurrent work already does this" | Overlapping-author ICML paper or recent arXiv | Cite anonymously, attach the PDF, give a one-line technical separation |
| "Optimization angle is incremental" | A new step-size or proximal variant | Show the regime where prior rates fail and yours holds, plus a tuned-baseline plot |
| "Benchmark-only contribution" | No mechanism, just leaderboard | Add an ablation tying the gain to the proposed component |
Worked vignette: a new optimizer with convergence theory
Suppose the paper proposes an adaptive-step method with a non-convex convergence guarantee plus deep-learning benchmarks. The related-work risk is that reviewers know Adam, AdaGrad, Lion, and the escaping-saddle and variance-reduction literature. Position it by separating the assumption set (smoothness, bounded variance, PL condition) your rate needs from what neighbors assume, naming the closest COLT/NeurIPS optimization theory, and conceding which benchmarks are shared rather than claiming a blanket win. The delta paragraph then reads as a precise rate-and-regime statement, not a list of beaten methods.
Output format
[Closest work] <3-5 papers or clusters>
[Concurrent ICML handling] none / cite anonymously / include PDF / split papers
[Incrementality risk] high / medium / low
[Technical delta] <one sentence>
[Related-work rewrite] <paragraph>
版本历史
- 1839142 当前 2026-07-05 13:19
