What is multi-model arbitration architecture in classification systems?

Multi-model arbitration uses a decision layer to choose or combine outputs from multiple classification models.

Instead of relying on a single model, systems run multiple specialized classifiers and use an arbitration layer to decide final output. Arbitration can be rule-based, learned (meta-model), or confidence-driven. This improves robustness and reduces single-model bias but increases complexity and latency.