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機器學習論文無程式碼被接受

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🤖閱讀原文： Reddit r/MachineLearning
#reproducibility#ml-conferences#sota-claimsml-conference-papersgithubopenreview

💡Reveals reproducibility crisis in ML conferences—check papers you cite

⚡ 30-Second TL;DR

有什麼變化

論文聲稱 SOTA 效能但無程式碼驗證

為什麼重要

侵蝕機器學習研究信任；推動會議強制程式碼發布政策。

下一步行動

Always search for and test GitHub code before replicating ML paper claims.

誰應關注：Researchers & Academics

關鍵要點

  • •論文聲稱 SOTA 效能但無程式碼驗證
  • •空 GitHub 儲存庫如蛋白質 MSA 的 RAG 方法
  • •擔憂捏造、資料洩漏或方法錯誤

🧠 深度解析

背景與延伸：來自公開資料，非原文內容。引用 9 個來源。

🔑 增強重點摘要

  • •Major conferences like AISTATS 2026 explicitly ban hidden LLM prompts in submissions, with policies to reject and report violators, including retroactive rejection post-acceptance[1].
  • •NeurIPS 2025 proceedings included over 100 papers with AI-hallucinated citations that survived peer review despite a 24.52% acceptance rate[7].
  • •ICML 2026 introduced a new policy capping reciprocal reviewers per person and regulating LLM use in reviewing to enhance integrity[3].
  • •TMLR journal paused new submissions from December 2025 to January 2026, amid broader efforts to manage rising ML paper volumes[9].

🔮 前景展望AI analysis grounded in cited sources

ML conferences will mandate code and data availability by 2027
Trends in AISTATS and ICML calls show escalating reproducibility requirements, building on open science policies already enforced in related venues like MSR 2026[1][3][2].
Peer review rejection rates for non-reproducible papers will rise 20%
Explicit bans on LLM misuse and hallucinated content in NeurIPS 2025 signal stricter verification, as conferences prioritize rigorous, verifiable claims[1][7].

⏳ 時間線

2025-12
NeurIPS 2025 publishes papers with 100+ AI-hallucinated citations surviving peer review
2025-11
TMLR announces submission pause into 2026 amid ML publication surge
2026-01
ICML 2026 releases call for papers with new LLM reviewing policy and optional attendance
🤖閱讀原文： Reddit r/MachineLearning
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同主題

探索 #reproducibility

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更多關於 ml-conference-papers

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