[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-language-models":3},{"tag":4,"articles":11},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":10},"3a123b8f-ad63-4875-82f2-2616713263ce","language models","language-models",3,"語言模型是生成式 AI 的核心，涵蓋預訓練、詞彙擴充、對齊與安全評估等議題。這裡會整理模型如何學習語意、處理新 token，以及在 jailbreak 與漏洞測試中暴露的風險。","Language models sit at the core of generative AI, spanning pretraining, token initialization, alignment, and security evaluation. This tag collects work on how LMs learn semantics, absorb new vocabulary, and where jailbreak tests expose failure modes.",[12,21],{"id":13,"slug":14,"title":15,"summary":16,"category":17,"image_url":18,"cover_image":18,"language":19,"created_at":20},"f07807ac-d51e-413e-a08a-42b6045d1e90","llms-implicit-grammar-representations-zh","LLM 學到文法了嗎？","這篇研究用線性 probe 讀取語言模型隱藏層，發現模型對「文法正確性」有獨立於字串機率的訊號，但在語意合理性上仍不如 likelihood。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778135468005-hzub.png","zh","2026-05-07T06:30:33.906328+00:00",{"id":22,"slug":23,"title":24,"summary":25,"category":17,"image_url":26,"cover_image":26,"language":19,"created_at":27},"7ec4baa4-f0af-441e-a97d-56f81a2ca854","avise-ai-security-evaluation-framework-zh","AVISE 模組化測 AI 安全漏洞","AVISE 是一個開源 AI 安全評估框架，主打模組化漏洞測試。論文用 25 個 jailbreak 測試案例與自動判定流程，驗證 9 個模型都能被攻破。","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1776924771424-kztu.png","2026-04-23T06:12:30.770582+00:00"]