[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-taskification":3},{"tag":4,"articles":9},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":8},"f74b35ab-fb57-49fe-849e-d9c659c214d8","taskification",2,null,[10],{"id":11,"slug":12,"title":13,"summary":14,"category":15,"image_url":16,"cover_image":16,"language":17,"created_at":18},"7459b8af-e677-4be6-a601-67ed8909a425","task-boundaries-can-skew-continual-learning-results-zh","任務邊界會扭曲持續學習","這篇 arXiv 論文指出，串流持續學習的任務切分不是小事；同一份資料流，只要任務邊界不同，評估結論就可能改變。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1777010816716-77s9.png","zh","2026-04-24T06:06:30.918134+00:00"]