No Single Best Model for Diversity: Router-Based Approach Selects Models Per-Prompt to Maximize Output Coverage
arXiv·medium signal
Researchers introduce diversity coverage as a metric measuring how comprehensively a model generates unique valid answers, and show no single LLM maximizes diversity across prompt types. Their learned router selects the best model per-prompt from a pool, outperforming any individual model on comprehensive answer generation. Practical for multi-model deployments where output variety matters (brainstorming, creative tasks, evaluation).