AI RESEARCH

Benchmarking Real-Time Question Answering via Executable Code Workflows

arXiv CS.CL

ArXi:2604.16349v1 Announce Type: cross Retrieving real-time information is a fundamental capability for search-integrated agents in real-world applications. However, existing benchmarks are predominantly static and therefore fail to capture the temporal dynamics of information and the continuously evolving nature of real-world knowledge. To address this limitation, we propose RT-QA, a dynamic evaluation framework that leverages executable code workflows to retrieve up-to-date answers at evaluation time.