[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-ml-conferences-tracker-deadlines-papers-zh":3,"tags-ml-conferences-tracker-deadlines-papers-zh":34,"related-lang-ml-conferences-tracker-deadlines-papers-zh":51,"related-posts-ml-conferences-tracker-deadlines-papers-zh":55,"series-tools-93a519c2-2902-4ccf-92a4-234277242bdb":92},{"id":4,"title":5,"content":6,"summary":7,"source":8,"source_url":9,"author":10,"image_url":11,"keywords":12,"language":22,"translated_content":10,"views":23,"is_premium":24,"created_at":25,"updated_at":25,"cover_image":11,"published_at":26,"rewrite_status":27,"rewrite_error":10,"rewritten_from_id":28,"slug":29,"category":30,"related_article_id":31,"status":32,"google_indexed_at":33,"x_posted_at":10,"tweet_text":10,"title_rewritten_at":10,"title_original":10,"key_takeaways":10,"topic_cluster_id":10,"embedding":10,"is_canonical_seed":24},"93a519c2-2902-4ccf-92a4-234277242bdb","ML 會議截止日追蹤器","\u003Cp>做 ML 論文，時間表常常比內容還煩。說真的，錯過 deadline，比模型掉 1% 還痛。\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fkhairulislam\u002FML-conferences\" target=\"_blank\" rel=\"noopener\">khairulislam\u002FML-conferences\u003C\u002Fa> 這個 GitHub 筆記本，就在解這個麻煩。\u003C\u002Fp>\u003Cp>它整理了會議日期、投稿截止日、地點，還有錄取論文清單。README 目前顯示 216 顆 stars、16 個 forks。對研究者來說，這種東西很土，但很實用。\u003C\u002Fp>\u003Cp>你不用一直切 \u003Ca href=\"https:\u002F\u002Ficml.cc\u002F\" target=\"_blank\" rel=\"noopener\">ICML\u003C\u002Fa>、\u003Ca href=\"https:\u002F\u002Fneurips.cc\u002F\" target=\"_blank\" rel=\"noopener\">NeurIPS\u003C\u002Fa>、\u003Ca href=\"https:\u002F\u002Ficlr.cc\u002F\" target=\"_blank\" rel=\"noopener\">ICLR\u003C\u002Fa> 官網。先看一張表，心裡就有底。這種整理，省的是腦力，不只是時間。\u003C\u002Fp>\u003Ch2>一份給 ML 人的期限索引\u003C\u002Fh2>\u003Cp>這個 repo 不是炫技網站。它就是一份乾淨的參考筆記。內容很直白：deadline、會期、地點、首頁連結、錄取名單。\u003C\u002Fp>\u003Cp>我覺得它好用的點，在於分類清楚。做視覺的人可以直接看 \u003Ca href=\"https:\u002F\u002Fcvpr.thecvf.com\u002F\" target=\"_blank\" rel=\"noopener\">CVPR\u003C\u002Fa>，做 NLP 的人可以看 \u003Ca href=\"https:\u002F\u002F2026.aclweb.org\u002F\" target=\"_blank\" rel=\"noopener\">ACL\u003C\u002Fa>。做系統研究的，也能切到 \u003Ca href=\"https:\u002F\u002Fmlsys.org\u002F\" target=\"_blank\" rel=\"noopener\">MLSys\u003C\u002Fa>。\u003C\u002Fp>\u003Cp>資料探勘、知識發現、軟體工程，也都有對應區塊。像 \u003Ca href=\"https:\u002F\u002Fkdd2026.kdd.org\u002F\" target=\"_blank\" rel=\"noopener\">KDD\u003C\u002Fa>、\u003Ca href=\"http:\u002F\u002Fcikm2025.org\" target=\"_blank\" rel=\"noopener\">CIKM\u003C\u002Fa>、\u003Ca href=\"https:\u002F\u002Fpakdd2026.org\u002F\" target=\"_blank\" rel=\"noopener\">PAKDD\u003C\u002Fa>，都能直接找到。對常跑 conference 的人，這比翻十幾個 CFP 頁面順手多了。\u003C\u002Fp>\u003Cul>\u003Cli>目前 snapshot 顯示 216 stars、16 forks\u003C\u002Fli>\u003Cli>用 Jupyter Notebook 寫，方便直接讀資料\u003C\u002Fli>\u003Cli>同時列 deadline、會期、錄取論文\u003C\u002Fli>\u003Cli>涵蓋 ML、CV、NLP、資料探勘、軟體工程\u003C\u002Fli>\u003Cli>有 Open、Closed、TBD 這類狀態標記\u003C\u002Fli>\u003C\u002Ful>\u003Cp>最近會議表是最常被看的部分。它把 2025 和 2026 的活動排在一起。你可以一次看到地點、截止日、首頁與狀態。\u003C\u002Fp>\u003Cp>像 \u003Ca href=\"https:\u002F\u002Ficml.cc\u002FConferences\u002F2026\" target=\"_blank\" rel=\"noopener\">ICML 2026\u003C\u002Fa>，列在 7 月 6 日到 12 日，地點是首爾，deadline 是 2026 年 1 月 28 日，狀態是 Open。這種資訊，對排實驗和寫初稿很直接。\u003C\u002Fp>\u003Cp>同一張表也看得出學術行程有多密。\u003Ca href=\"https:\u002F\u002F2026.ijcai.org\u002F\" target=\"_blank\" rel=\"noopener\">IJCAI 2026\u003C\u002Fa> 在不來梅，\u003Ca href=\"https:\u002F\u002Fconferences.miccai.org\u002F2026\u002Fen\u002F\" target=\"_blank\" rel=\"noopener\">MICCAI 2026\u003C\u002Fa> 在阿布達比，\u003Ca href=\"https:\u002F\u002Fkdd2026.kdd.org\u002F\" target=\"_blank\" rel=\"noopener\">KDD 2026\u003C\u002Fa> 在濟州。這些不是八卦，是排程依據。\u003C\u002Fp>\u003Ch2>為什麼研究者會需要它\u003C\u002Fh2>\u003Cp>conference deadline 不是小事。它會影響實驗節奏、寫作節奏，還有 lab 內部的 review 安排。對 startup 來說，甚至會影響招募和產品曝光的節點。\u003C\u002Fp>\u003Cp>這個 repo 的價值，是把分散的資訊收斂起來。你不用每次重新讀 CFP。直接比一比，就知道哪個 venue 還開著，哪個已經關門。\u003C\u002Fp>\u003Cp>錄取論文清單也很有用。它不是只告訴你日期。它也讓你看見某一年到底收了什麼題目。這對找趨勢、看主題熱度、判斷題目適配度，都有幫助。\u003C\u002Fp>\u003Cblockquote>“The best way to predict the future is to invent it.” — Alan Kay\u003C\u002Fblockquote>\u003Cp>Alan Kay 這句話常被拿來講研究圈。原因很簡單。會盯 deadline、看錄取論文的人，通常也是下一輪題目最早動手的人。\u003C\u002Fp>\u003Cp>這個 notebook 做的，是行政雜事。它不評分，也不排名。它只是把投稿流程講清楚。講白了，這在 ML 圈很重要，因為日期常常變，窗口又短。\u003C\u002Fp>\u003Cp>Notebook 格式還有一個好處。它很好維護。有人要補新資料，只要加一列、改一個連結，不必重做整個網站。對社群型資源來說，這種低摩擦很關鍵。\u003C\u002Fp>\u003Ch2>和官方網站比起來差在哪\u003C\u002Fh2>\u003Cp>官方 conference 頁面才是第一手來源。這點沒爭議。問題是，它們很難直接比較。有的把 schedule 放首頁，有的把 deadline 藏在 CFP，有的還會改網址。\u003C\u002Fp>\u003Cp>這個 repo 的做法很務實。它把那些亂七八糟的格式，統一成一張表。你可以直接橫向比對，不用在不同網站之間來回跳。\u003C\u002Fp>\u003Cp>這件事特別有感，因為 ML 大會的節奏本來就不同。\u003Ca href=\"https:\u002F\u002Ficml.cc\u002FConferences\u002F2025\" target=\"_blank\" rel=\"noopener\">ICML 2025\u003C\u002Fa> 在溫哥華，\u003Ca href=\"https:\u002F\u002Fneurips.cc\u002FConferences\u002F2025\" target=\"_blank\" rel=\"noopener\">NeurIPS 2025\u003C\u002Fa> 在聖地牙哥，\u003Ca href=\"https:\u002F\u002Ficlr.cc\u002FConferences\u002F2025\u002FDates\" target=\"_blank\" rel=\"noopener\">ICLR 2025\u003C\u002Fa> 在新加坡。這些日期差，會直接影響團隊怎麼排實驗。\u003C\u002Fp>\u003Cul>\u003Cli>\u003Ca href=\"https:\u002F\u002Ficml.cc\u002FConferences\u002F2026\" target=\"_blank\" rel=\"noopener\">ICML 2026\u003C\u002Fa>：7\u002F6–7\u002F12，首爾，1\u002F28 截止，Open\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002F2026.ijcai.org\u002F\" target=\"_blank\" rel=\"noopener\">IJCAI 2026\u003C\u002Fa>：8\u002F15–8\u002F21，不來梅，1\u002F19 截止，Open\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fconferences.miccai.org\u002F2026\u002Fen\u002F\" target=\"_blank\" rel=\"noopener\">MICCAI 2026\u003C\u002Fa>：10\u002F4–10\u002F8，阿布達比，2\u002F26 截止，Open\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fkdd2026.kdd.org\u002F\" target=\"_blank\" rel=\"noopener\">KDD 2026\u003C\u002Fa>：8\u002F9–8\u002F13，濟州，2\u002F8 截止，Open\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fcvpr.thecvf.com\u002FConferences\u002F2026\" target=\"_blank\" rel=\"noopener\">CVPR 2026\u003C\u002Fa>：6\u002F6–6\u002F12，丹佛，11\u002F13 截止，Closed\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Ficcv.thecvf.com\u002F\" target=\"_blank\" rel=\"noopener\">ICCV 2025\u003C\u002Fa>：10\u002F19–10\u002F25，檀香山，3\u002F7 截止，Closed\u003C\u002Fli>\u003C\u002Ful>\u003Cp>這個 repo 還有歷史價值。ICML 區塊可以追到 2008 年，NeurIPS 也有多個年份。你可以看出會議怎麼換城市，deadline 怎麼漂移，還有哪些主題慢慢變成主流。\u003C\u002Fp>\u003Cp>它也會連到 DBLP。DBLP 是學術索引老牌資料源。把它跟 repo 的表格搭一起看，方便又能查證。這種做法很樸素，但我覺得比花俏介面更可靠。\u003C\u002Fp>\u003Ch2>它其實像一個社群工具\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fkhairulislam\u002FML-conferences\" target=\"_blank\" rel=\"noopener\">ML-conferences\u003C\u002Fa> 值得收藏，是因為它把無聊問題處理得很好。研究者不需要另一個很會講故事的 dashboard。大家要的是一份能在 1 分鐘內掃完的清單。\u003C\u002Fp>\u003Cp>它也示範了，簡單 notebook 可以變成社群基礎設施。它介於私人備忘錄和公開工具之間。這個位置很尷尬，但也很有用。\u003C\u002Fp>\u003Cp>如果 maintainer 持續更新 recent-conferences 表，補上錄取論文連結，這份筆記本很可能會變成很多 ML 作者的第一個分頁。真正的考驗，是社群會不會持續補資料。\u003C\u002Fp>\u003Cp>畢竟 conference 日期會動，CFP 頁面會搬家，新 venue 也會冒出來。這種工具要活，靠的不是華麗，而是更新速度。\u003C\u002Fp>\u003Ch2>接下來怎麼看這類工具\u003C\u002Fh2>\u003Cp>我猜這類 repo 會越來越重要。原因很簡單。ML 論文數量還在多，會議也沒有變少。對研究者來說，資訊整理本身就是成本。\u003C\u002Fp>\u003Cp>如果你現在正在排投稿，我會建議先把這種清單加進書籤。再回官方頁面核對一次。這樣最穩，也最省時間。\u003C\u002Fp>\u003Cp>下一次你準備送 paper 前，先問自己一個問題：你的目標 venue 還開著嗎？如果答案是否定的，那就別再拖了。先改計畫，比硬拚更實際。\u003C\u002Fp>","GitHub 筆記本整理 ICML、NeurIPS、ICLR、CVPR、ACL 等 ML 會議的截止日、會期與錄取論文，適合研究者快速排程。","github.com","https:\u002F\u002Fgithub.com\u002Fkhairulislam\u002FML-conferences",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Fcover-1774617054017-p2t3pl.png",[13,14,15,16,17,18,19,20,21],"ML conference","deadline tracker","GitHub 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定價其實比看起來更便宜","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778869845081-j4m7.png","2026-05-15T18:30:25.797639+00:00",{"id":63,"slug":64,"title":65,"cover_image":66,"image_url":66,"created_at":67,"category":30},"68e4be16-dc38-4524-a6ea-5ebe22a6c4fb","why-vidhub-huiyuan-hutong-bushi-quan-shebei-tongyong-zh","為什麼 VidHub 會員互通不是「買一次全設備通用」","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778789450987-advz.png","2026-05-14T20:10:24.048988+00:00",{"id":69,"slug":70,"title":71,"cover_image":72,"image_url":72,"created_at":73,"category":30},"7a1e174f-746b-4e82-a0e3-b2475ab39747","why-buns-zig-to-rust-experiment-is-right-zh","為什麼 Bun 的 Zig-to-Rust 實驗是對的","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778767879127-5dna.png","2026-05-14T14:10:26.886397+00:00",{"id":75,"slug":76,"title":77,"cover_image":78,"image_url":78,"created_at":79,"category":30},"e742fc73-5a65-4db3-ad17-88c99262ceb7","why-openai-api-pricing-is-product-strategy-zh","為什麼 OpenAI API 定價是產品策略，不是註腳","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778749859485-chvz.png","2026-05-14T09:10:26.003818+00:00",{"id":81,"slug":82,"title":83,"cover_image":84,"image_url":84,"created_at":85,"category":30},"c757c5d8-eda9-45dc-9020-4b002f4d6237","why-claude-code-prompt-design-beats-ide-copilots-zh","為什麼 Claude Code 的提示設計贏過 IDE Copilot","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778742645084-dao9.png","2026-05-14T07:10:29.371901+00:00",{"id":87,"slug":88,"title":89,"cover_image":90,"image_url":90,"created_at":91,"category":30},"4adef3ab-9f07-4970-91cf-77b8b581b348","why-databricks-model-serving-is-right-default-zh","為什麼 Databricks Model Serving 是生產推論的正確預設","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778692245329-a2wt.png","2026-05-13T17:10:30.659153+00:00",[93,98,103,108,113,118,123,128,133,138],{"id":94,"slug":95,"title":96,"created_at":97},"de769291-4574-4c46-a76d-772bd99e6ec9","googles-biggest-gemini-launches-in-2026-zh","Google 2026 最大 Gemini 盤點","2026-03-26T07:26:39.21072+00:00",{"id":99,"slug":100,"title":101,"created_at":102},"855cd52f-6fab-46cc-a7c1-42195e8a0de4","surepath-real-time-mcp-policy-controls-zh","SurePath 推出即時 MCP 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深度對比：202…","2026-03-26T13:27:14.279193+00:00",{"id":129,"slug":130,"title":131,"created_at":132},"0975afa1-e0c7-4130-a20d-d890eaed995e","practical-github-guide-learning-ml-2026-zh","2026 機器學習入門 GitHub 實用指南","2026-03-27T01:16:49.712576+00:00",{"id":134,"slug":135,"title":136,"created_at":137},"bfdb467a-290f-4a80-b3a9-6f081afb6dff","aiml-2026-student-ai-ml-lab-repo-review-zh","AIML-2026：像課綱的學生實驗 Repo","2026-03-27T01:21:51.467798+00:00",{"id":139,"slug":140,"title":141,"created_at":142},"80cabc3e-09fc-4ff5-8f07-b8d68f5ae545","ai-trending-github-repos-and-research-feeds-zh","AI Trending：把 AI 資源收成一張表","2026-03-27T01:31:35.262183+00:00"]