[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-transformer":3},{"tag":4,"articles":10},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":9},"1b756de5-5b17-4f34-8968-d2df19807253","transformer",3,"Transformer 是處理序列資料的核心架構，從文字生成、圖像擴散到日誌異常偵測都常見其身影。它關注注意力機制、長距依賴與推論效率，也延伸到壓縮位元組、生成多樣性與交易系統等實作場景。","Transformer is the sequence model behind many modern AI systems, from language generation and text-to-image diffusion to log anomaly detection. Coverage here focuses on attention, long-range dependencies, efficiency tradeoffs, and applied variants such as compressed-byte inference and diversity control.",[11,20],{"id":12,"slug":13,"title":14,"summary":15,"category":16,"image_url":17,"cover_image":17,"language":18,"created_at":19},"50db75e4-31d8-4222-9f32-476b682a3848","humanoid-gpt-zero-shot-motion-tracking-en","Humanoid-GPT scales motion tracking with a GPT-style model","Humanoid-GPT uses a GPT-style Transformer and 2B motion frames to improve zero-shot whole-body motion tracking.","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780469286641-cfel.png","en","2026-06-03T06:47:34.975723+00:00",{"id":21,"slug":22,"title":23,"summary":24,"category":16,"image_url":25,"cover_image":25,"language":18,"created_at":26},"8a875d5c-c22a-4eac-b1c0-3a696f91079d","implicit-channel-estimation-full-duplex-mimo-en","Implicit Channel Estimation for Full-Duplex MIMO","A transformer learns site-specific beams from few measurements, avoiding explicit self-interference channel estimation.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1779607558066-pp80.png","2026-05-24T07:25:33.435391+00:00"]