Resolving the Robustness-Precision Trade-off in Financial RAG through Hybrid Document-Routed Retrieval

ArXi:2603.26815v1 Announce Type: cross Retrieval-Augmented Generation (RAG) systems for financial document question answering typically follow a chunk-based paradigm: documents are split into fragments, embedded into vector space, and retrieved via similarity search. While effective in general settings, this approach suffers from cross-document chunk confusion in structurally homogeneous corpora such as regulatory filings.