DAIR.AI@dair_aiOct 5

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: https://t.co/GimGee8u8V Chat with Paper: https://t.co/0GOcC169at