# RouteDRAG

In multimodal long-document question answering, agentic retrieval is not always worth its extra computation and can even hurt answer accuracy. RouteDRAG makes both whether to invoke an agent and how it then executes into learned choices: a graph-backed index organizes cross-page, table and figure content, path routing predicts the benefit of an agent over shorter paths, and dynamic execution controls tool use and termination. Across two benchmarks it assigns only 79.3% of queries to an agent while averaging 3.47 percentage points higher accuracy than shorter-path-only execution, and it also surpasses uniform agent execution with fewer answering calls.

In multimodal long-document question answering, agentic retrieval is not always worth its extra computation and can even hurt answer accuracy. RouteDRAG makes both whether to invoke an agent and how it then executes into learned choices: a graph-backed index organizes cross-page, table and figure content, path routing predicts the benefit of an agent over shorter paths, and dynamic execution controls tool use and termination. Across two benchmarks it assigns only 79.3% of queries to an agent while averaging 3.47 percentage points higher accuracy than shorter-path-only execution, and it also surpasses uniform agent execution with fewer answering calls.