LLM-generated coordination graph priors improve multi-agent reinforcement learning performance on MPE benchmarks, with models as small as 1.5B parameters proving effective.
HierRouter: Coordinated routing of specialized large language models via reinforcement learning
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The Workload-Router-Pool architecture is a 3D framework for LLM inference optimization that synthesizes prior vLLM work into a 3x3 interaction matrix and proposes 21 research directions at the intersections.
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Do LLM-derived graph priors improve multi-agent coordination?
LLM-generated coordination graph priors improve multi-agent reinforcement learning performance on MPE benchmarks, with models as small as 1.5B parameters proving effective.
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The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
The Workload-Router-Pool architecture is a 3D framework for LLM inference optimization that synthesizes prior vLLM work into a 3x3 interaction matrix and proposes 21 research directions at the intersections.