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Notes on routing
6 notes
You Cannot Pick a Provider From the Price List: Market-Aware Routing for Open-Weight LLM Inference
The preprint argues that open-weight inference routing must choose both a model and the provider serving it. Across live endpoints, models, task types, and three measurement waves, it reports that the same model can…
Learning the Cost of Reliable Inference
The paper proposes a procurement platform where model providers compete on task-level token prices through a reverse second-price auction. The platform learns provider quality and routes requests to a cost-competitive…
Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation
Researchers have developed a system that routes AI queries to the most effective and efficient model based on costly value estimation. The system, called Pandora's Router, uses a trade-off between fast but noisy…
Scrouting: Cost-Aware Routing of Coding Agents by Scouting the Repository First
The researchers introduce SuperScout, a cost-effective solution for routing language models to resolve software issues in repositories. SuperScout first explores the repository and produces a structured handoff, which…
Agentic Routing: The Harness-Native Data Flywheel
The authors propose a new method of model selection for large language model agents called Harness-Native agentic routing. This method selects the best-fit model or multiple complementary models based on the full…
Linguistic Firewall: Geometry as Defense in Multi-Agent Systems Routing
A new routing architecture called ANTAP (Automatic Non-Textual Agent Picker) was introduced in this research. It aims to address security vulnerabilities in multi-agent systems by discarding indirect proxies and…
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