AI RESEARCH
ATLAS: Agentic Test-time Learning-to-Allocate Scaling
arXiv CS.LG
•
ArXi:2606.01667v1 Announce Type: new Test-time scaling has become a major way to improve large language model reasoning, but its orchestration has remained designer-engineered: a fixed sample budget, a fixed refinement loop, a fixed scoring rule, or a fixed search policy decides how compute is spent, leaving the model in charge of solving but not of orchestration. We