# Wiki Foundation Model retrieves agent memory from linked markdown wikis

WFM turns an LLM wiki into a graph and retrieves with query-conditioned message passing, so page text and the links between pages shape the result together. The team says a GPU-to-GPU training protocol trains 10.5 times faster and reports strong results on five agent-memory and multi-hop reasoning benchmarks.

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Source: elvis · Published 9/22/2026, 19:17:21

The Wiki Foundation Model (WFM) is for agents whose long-term memory is a folder of linked markdown files. It turns an LLM wiki into a graph and retrieves with message passing conditioned on the query, so the dense text on each page and the links between pages shape the result together.

The team also built a GPU-to-GPU training protocol that it says trains 10.5 times faster, and it reports strong results on five benchmarks covering agent memory and multi-hop reasoning. The work is described in the [WFM paper](https://arxiv.org/abs/2609.18182), and academy.dair.ai hosts a [chat page for the paper](https://academy.dair.ai/papers/wfm-wiki-foundation-model-for-complex-agentic-reasoning-2609.18182).

Tags: WFM, Agent memory, LLM wiki, Research

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