CRAI: Calibrated Regret-Aware LLM Invocation for Efficient Cloud Resource Scheduling
Large language models can contribute semantic and strategic reasoning to cloud schedulers, but invoking a large model at every scheduling epoch converts inference latency and monetary cost into a control-plane bottleneck. This paper studies the invocation decision itself. We present CRAI, a calibrated regret-aware invo...