The agentic system with teacher-bandit planning and distillation to a student model reduces latency by 23% while achieving 89% plan replication accuracy and 15x faster inference on NYC Taxi and IMDB datasets.
Chen et al., ”Transformer-based query optimization with attention mechanisms,”ACM Trans
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Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics
The agentic system with teacher-bandit planning and distillation to a student model reduces latency by 23% while achieving 89% plan replication accuracy and 15x faster inference on NYC Taxi and IMDB datasets.