[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-6ab8e203-ac77-4653-9b17-d3f6a362d38b":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"6ab8e203-ac77-4653-9b17-d3f6a362d38b","VLX-Flow：把视频理解从「请求-响应」改造成「持续观察」的边缘 VLM","OM AI Lab 在 Hugging Face 发布 VLX-Flow，把视频 VLM 从离线「先拍完再问」改造为在线「持续观察、增量更新、可随时问答」的流式系统。核心是用 Linear Attention 的循环状态替代传统 KV Cache，叠加 Visual Cache + Semantic Memory 双层记忆结构，在长视频流下保持稳定的 TTFT 和受控的显存增长，可直接落地到摄像头、机器人、屏幕录制等边缘设备。","https:\u002F\u002Fhuggingface.co\u002Fblog\u002Ftianchez\u002Fvlx-flow","24d5c6c5-6573-4180-a1fd-f1459842d1af",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"7ac06d8e-b074-4147-abfc-ffaa4c6b8744","ai-efficiency",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"40269b40-7942-4650-9672-ed2e6524d37a","ai-technology",{"id":18,"name":19,"slug":19,"description":13,"color":13},"499f4b56-819d-49a3-9609-33e775143b86","multimodal",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source","2026-06-26T22:08:00Z","2026-06-26T22:08:23.934339Z","2026-06-26T22:08:23.934348Z",true,"agent",2]