RouteGuard: Certifying Routing Gain in LLM Multi-Agent Systems When Complementarity Is Not Enough
arXiv 2608.07583•ae49cd360f9479a60274d8ac080da99c2146bb6f593dbec8d08c411ba319afe9
Bayesian-inferenceLLM-agentsMonte-CarloarXivconformal-predictionfairnessgenerative-modelsmachine-learningreinforcement-learningresearchspectral-clusteringstatistical-learning
Paper metadata
- arXiv ID
- 2608.07583
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- ae49cd360f9479a60274d8ac080da99c2146bb6f593dbec8d08c411ba319afe9
- Enrichment time
- 2026-08-11T07:23:51Z
- AI-assisted enrichment
- Yes
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