WFM 是一个 Wiki Foundation Model，把 LLM Wiki 转成图结构，用基于查询条件的消息传递同时利用页面文本与链接结构进行检索。团队还构建了 GPU-to-GPU 训练协议，训练速度提升 10.5 倍，并在五个智能体记忆与多跳推理基准上取得强劲结果。若你的智能体长期记忆是链接式 Markdown 文件夹，WFM 正是为此格式设计。
Interesting paper on agent memory stored as a linked markdown wiki.
Lots of great ideas and insights if you work with LLM Wikis.
Wikis are useful for agents because each page holds dense text and the links between pages hold structure. WFM is a Wiki Foundation Model trained to use both at once.
It turns an LLM Wiki into a graph and retrieves from it with message passing conditioned on the query, so the text of each page and the link structure shape the result together.
The team also built a GPU-to-GPU training protocol that trains 10.5x faster, and reports strong results on five agent memory and multi-hop reasoning benchmarks.
If your agent's long-term memory is a folder of linked markdown files, WFM is designed for that format.
Paper: https://t.co/t3iwlcCFB8
Chat with Paper: https://t.co/4QL4IyKPBW
来源：@omarsar0 · x.com