# WFM：把智能体记忆存成链接式 Markdown Wiki

- 来源：elvis (@omarsar0)
- 发布时间：2026-09-23 10:05
- AIHOT 分数：38
- AIHOT 链接：https://aihot.news/items/cmudgu9hx0a5zroggdtbtpfbw
- 原文链接：https://x.com/omarsar0/status/2102579964436680959

## AI 摘要

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做检索，让每页文本与页面间链接结构共同决定结果。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一堆链接的 Markdown 文件，WFM 正是为此格式设计。

## 正文

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://arxiv.org/abs/2609.18182

Chat with Paper: https://academy.dair.ai/papers/wfm-wiki-foundation-model-for-complex-agentic-reasoning-2609.18182