WFM: agent memory as a linked Markdown wiki
The paper proposes Wiki Foundation Model, which turns an LLM wiki into a graph and retrieves from it with query-conditioned message passing, plus a training protocol that runs 10.5x faster.
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