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cs.AI2026
Encoded Early, Used Late: Where Transformers Begin to Act on an Inferred Partner's Expertise
Mika Okamoto, Gabriele Sarti
A transformer can make an attribute linearly decodable in its residual stream at a depth where that attribute does not yet influence the output. This gap between where information…
cs.AI2026
Explainable Model Routing for Agentic Workflows
Mika Okamoto, Ansel Kaplan Erol, Mark Riedl
Modern agentic workflows decompose complex tasks into specialized subtasks and route them to diverse models to minimize cost without sacrificing quality. However, current routing a…
cs.AI2026
Trust by Design: Skill Profiles for Transparent, Cost-Aware LLM Routing
Mika Okamoto, Ansel Kaplan Erol, Glenn Matlin
How should Large Language Model (LLM) practitioners select the right model for a task without wasting money? We introduce BELLA (Budget-Efficient LLM Selection via Automated skill-…