[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-分布匹配":3},{"tag":4,"articles":9},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":8},"fd9ed94c-7bcb-42cb-8aaf-be597c02cd8e","分布匹配",0,null,[10],{"id":11,"slug":12,"title":13,"summary":14,"category":15,"image_url":16,"cover_image":16,"language":17,"created_at":18},"63eabb4a-63f4-4ea4-b959-85470c2e5691","why-distribution-fine-tuning-beats-sft-writing-zh","為什麼 Distribution Fine Tuning 比 SFT 更適合 …","Distribution Fine Tuning 比 SFT 更適合 LLM 寫作，因為它更接近人類文本的分布，而不是只學會表面格式。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1779321829749-q04l.png","zh","2026-05-21T00:03:24.901131+00:00"]