微软等提出 CorpusMap，为智能体检索语料预建实体导航层
微软等提出 CorpusMap，在智能体检索大型文档集合前预先解析跨文档的重复实体，为每个实体建页并链接到所有提及它的文档，原文档保持原位；智能体读取文档后可沿实体跳转到相关文档，避免重复搜索同一证据。
Banger paper from Microsoft and colleagues.
If you run agents that search a large document collection, this one is worth your time.
(bookmark it)
They introduce CorpusMap, which resolves recurring entities across the collection in advance and gives each entity a page that links to every document that mentions it.
The original documents stay in place.
The agent reads a document, follows an entity to related documents, and avoids searching for the same evidence again.
Across 7 models and three benchmarks, answer quality goes up 6.4 to 11.7 points while input tokens drop 34% to 57%.
It also beats an LLM Wiki layer and three other navigation layers.
The map can be built without LLM calls and updated as new documents arrive.
Paper: arxiv.org/abs/2609.37226
Chat with Paper: academy.dair.ai/papers/follo…
来源：dair_ai · x.com