技能 人工智能 NeurIPS相关工作撰写指南

NeurIPS相关工作撰写指南

v20260724
neurips-related-work
本指南指导作者如何撰写“相关工作”部分,确保论文的创新点和技术优势能够准确且有力地定位在复杂的学术背景中。它帮助作者对比相邻会议、最新的预印本,并精确定位与现有方法的技术差异,从而最大程度降低学术定位风险,适用于顶会投稿。
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NeurIPS Related Work

Use this skill when novelty or positioning is the main risk. NeurIPS reviewers will often know recent papers from neighboring AI venues and preprint streams; stale comparisons are a serious weakness.

What to cover

  • Direct technical ancestors: methods with the same objective, architecture, proof technique, benchmark, dataset, or deployment problem.
  • Neighboring venues: ICML, ICLR, AAAI, IJCAI, AISTATS, UAI, COLT, MLSys, KDD, CVPR, ACL, EMNLP, SIGIR, ICRA, CHI, and other subfield venues as relevant.
  • Contemporaneous work: papers that appeared during the current review window. The 2026 handbook treats work appearing online after March 1, 2026 as contemporaneous for review purposes, but authors still need to cite and discuss it when feasible.
  • Preprints: public preprints are not automatically disqualifying, but they must not be used to advertise a submission aggressively under review.

Delta-writing template

For each close paper, write:

<Prior work> solves <problem> by <mechanism>. It does not address <gap>.
Our paper differs by <technical delta>, which matters because <evidence or theory>.

Failure modes

  • Listing citations without explaining technical differences.
  • Omitting a close arXiv or prior conference paper because it is inconvenient.
  • Claiming novelty over broad topic labels rather than mechanisms.
  • Hiding dependence on prior code, data, prompts, or evaluation protocols.

Output format

[Closest prior work] <3-5 papers or categories>
[Missing citation risk] High / Medium / Low
[Technical delta] <one-sentence difference>
[Contemporaneous work handling] <cite/compare/acknowledge>
[Rewrite] <related-work paragraph>
信息
Category 人工智能
Name neurips-related-work
版本 v20260724
大小 1.92KB
更新时间 2026-07-28
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