11h ago
MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings
★★★★★
significance 3/5
Researchers have developed MTRouter, a system designed to optimize the cost-performance trade-off in multi-turn LLM interactions. By using joint history-model embeddings, the system intelligently selects the most efficient model for each turn, significantly reducing inference costs compared to high-end models like GPT-5.
Why it matters
Optimizing inference costs through intelligent routing is essential for the economic scalability of complex, multi-turn agentic workflows.
Tags
#llm routing #inference cost #multi-turn interaction #optimization #embeddingsRelated coverage
- Global South OpportunitiesPivotal Research Fellowship 2026 (Q3): AI Safety Research Opportunity - Global South Opportunities
- arXiv cs.AIAn Intelligent Fault Diagnosis Method for General Aviation Aircraft Based on Multi-Fidelity Digital Twin and FMEA Knowledge Enhancement
- arXiv cs.AIPExA: Parallel Exploration Agent for Complex Text-to-SQL
- arXiv cs.AIThe Power of Power Law: Asymmetry Enables Compositional Reasoning
- arXiv cs.AIOn the Existence of an Inverse Solution for Preference-Based Reductions in Argumentation