[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-robustness":3},{"tag":4,"articles":9},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":8},"09bb9c45-1eee-4874-899f-51829dfb3b44","robustness",1,null,[10,19],{"id":11,"slug":12,"title":13,"summary":14,"category":15,"image_url":16,"cover_image":16,"language":17,"created_at":18},"9f629b51-c1ad-4a83-beef-40059da1ab54","llms-stumble-counterintuitive-probability-zh","LLM 在反直覺機率題翻車","這篇研究發現，LLM 在標準機率題表現很高，但遇到反直覺、改寫或帶誤導提示的題目時，準確率會明顯下滑。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780900377752-3uk6.png","zh","2026-06-08T06:32:28.84056+00:00",{"id":20,"slug":21,"title":22,"summary":23,"category":15,"image_url":24,"cover_image":24,"language":17,"created_at":25},"85a3dfd4-9f87-4028-8ec1-44636ec804b8","why-fine-tuning-still-beats-prompt-only-ai-zh","為什麼微調仍然勝過只靠提示詞的 AI","微調仍是把基礎模型做成可靠專用工具的最佳方法，因為它改變模型本身，而不只是包裝在外的提示詞。","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780120970410-mtab.png","2026-05-30T06:02:21.657693+00:00"]