ARTFEED — Contemporary Art Intelligence

MetaRoute-Bench: A New Framework for Evaluating Agentic Workflow Routing Policies

ai-technology · 2026-08-04

MetaRoute-Bench has been introduced to evaluate how decisions are made in agentic systems, which often encounter choices like whether to answer questions directly, break tasks down, use tools, run code, consult experts, verify results, or recover from mistakes. These decisions impact how well tasks are completed, their costs, and the time taken, but they’re typically only assessed through overall task accuracy. This benchmark provides a clear and open way to analyze these decision-making processes within a single execution model. It includes 180 synthetic task profiles in areas like data analysis and document processing, and features eight routing policies and 30 random seed pairs. A task-aware policy achieved a 79.4% success rate, surpassing other approaches. The benchmark is available on arXiv with the identifier 2608.00107.

Key facts

  • MetaRoute-Bench is an open, inspectable framework for comparing meta-decision policies.
  • The benchmark contains 180 synthetic task profiles.
  • Task profiles span data analysis, research, and document processing.
  • Eight routing policies are evaluated.
  • 30 paired random seeds are used.
  • 43,200 traces were analyzed.
  • A task-aware compositional policy achieved 79.4% success.
  • A workload-specific static policy achieved 76.7% success.
  • One-shot task routing achieved 67.4% success.
  • Direct answering achieved 52.9% success.
  • The task-aware policy outperformed the static policy by 2.7 percentage points.
  • The benchmark is available on arXiv with identifier 2608.00107.

Entities

Institutions

  • arXiv

Sources