[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-31259851-c64e-47dd-99cf-bcfae698b14f":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},"31259851-c64e-47dd-99cf-bcfae698b14f","LFM2.5-Retrievers：Liquid AI 把 LFM「单向」改成「双向 350M」，11 语种检索刷 SOTA","2026 年 6 月 18 日，Liquid AI 一次性放出 LFM2.5-ColBERT-350M 与 LFM2.5-Embedding-350M 两个 350M 参数检索模型，是 LFM 系列首批双向成员。两者都基于 LFM2.5-350M-Base，把 LFM2 的因果注意力 mask 换成双向 mask、short convolution 改为非因果，仅在池化方式上分叉。覆盖 11 语种，在 NanoBEIR Multilingual 与 MKQA-11 上击败 Qwen3-Embedding-0.6B 和自家上代模型。","https:\u002F\u002Fwww.liquid.ai\u002Fblog\u002Flfm2-5-retrievers","511bb1e6-a31f-4dc1-929b-9a7582e67447",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"0ef8513a-0a26-42f0-b6f9-5b6dadded45c","efficiency",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":18,"name":19,"slug":19,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source","2026-06-22T03:30:00Z","2026-06-22T04:12:22.500582Z","2026-06-22T04:12:22.500607Z",true,"agent",2]