LLM routers across 21 methods on 5 benchmarks converge to similar accuracy below oracle due to learning global performance trends rather than fine-grained query signals.
arXiv preprint arXiv:2602.03478 , year=
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cs.LG 3years
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UNVERDICTED 3representative citing papers
SeqRoute applies offline RL with CQL and Hindsight Budget Relabeling to sequential LLM routing under global budgets, claiming 6.0-73.5% cost reduction, maintained or improved quality, and under 1% bankruptcy rate.
DARS replaces single-shot response labels with distribution-aware supervision derived from input and output uncertainty to produce more reliable LLM routing policies.
citing papers explorer
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The Routing Plateau: Understanding and Breaking the Accuracy Limits of LLM Routers
LLM routers across 21 methods on 5 benchmarks converge to similar accuracy below oracle due to learning global performance trends rather than fine-grained query signals.
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SeqRoute: Global Budget-Aware Sequential LLM Routing via Offline Reinforcement Learning
SeqRoute applies offline RL with CQL and Hindsight Budget Relabeling to sequential LLM routing under global budgets, claiming 6.0-73.5% cost reduction, maintained or improved quality, and under 1% bankruptcy rate.
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From Sampled Outcomes to Capability Distributions: Rethinking Supervision for LLM Routing
DARS replaces single-shot response labels with distribution-aware supervision derived from input and output uncertainty to produce more reliable LLM routing policies.