Drift-Aware LLM Routing with Sparse Contexts and Shared Budgets
cs.AI
Submitted: 2026-09-01
Updated: 2026-09-01
Terminology
Sources
- FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
- A Unified Approach to Routing and Cascading for LLMs
- RouterBench: A Benchmark for Multi-LLM Routing System
- Online Stochastic Optimization with Wasserstein Based Non-stationarity
- RouteLLM: Learning to Route LLMs with Preference Data
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
- VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection