English(EN) On writing papers [D]

AI研究人员讨论有效的科学论文撰写策略

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-13 18:18

Reddit上的r/MachineLearning版块正在讨论撰写科学论文的有效策略，特别是针对NeurIPS、ICLR和ICML等顶级会议。参与者正在寻求关于各种写作风格和方法的建议。讨论的一个关键点是Michael J. Black的一篇博文，他提倡采用更具故事性的论文写作方法，这与纯粹以结果为导向的方法形成对比。 AI

影响提供了对AI研究界学术出版规范的见解。

排序理由讨论学术论文的写作策略，而非新发布或重要的行业事件。

在 r/MachineLearning 阅读 →

NeurIPS
ICLR

论文

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 1 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Commentary; 讨论学术论文的写作策略，而非新发布或重要的行业事件。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: Standard; On-topic for AI-industry coverage; kept in the public index.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

r/MachineLearning TIER_1 English(EN) · /u/ComprehensiveTop3297 · 2026-10-13 18:18

关于写论文[D]

<div class="md"><p>Hey all, </p> <p>I was curious about your take on writing papers. I see many different styles of writing, and I am kind of lost myself about what the best way to write is for a NeurIPS/ICLR/ICML conference audience. Do you have any tips or though…

本文如何被排名

报道来源 [1]

关于写论文[D]

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