GRADE: Optimizing Multi-Agent Inference Costs via Gated Routing
Tanmoy_Chak · x · 2026-08-13
While powerful, multi-agent systems often multiply inference costs due to fixed pipelines. The paper introduces GRADE (Gated Routing and Adaptive Depth for Efficient Reasoning) to optimize multi-agent reasoning by adapting computation per query.
Key highlights include:
- Learned Coordination: A hierarchical system governed by lightweight gates dynamically manages agent selection, routing depth, communication, and pruning per query.
- CoGRPO Training: Adapts the GRPO RL recipe into a critic-free approach, assigning a shared advantage signal to all participating agents and gates during a rollout.
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