AI RESEARCH

Spend Less, Reason Better: Budget-Aware Value Tree Search for LLM Agents

arXiv CS.AI

ArXi:2603.12634v1 Announce Type: cross Test-time scaling has become a dominant paradigm for improving LLM agent reliability, yet current approaches treat compute as an abundant resource, allowing agents to exhaust token and tool budgets on redundant steps or dead-end trajectories. Existing budget-aware methods either require expensive fine-tuning or rely on coarse, trajectory-level heuristics that cannot intervene mid-execution. We propose the Budget-Aware Value Tree (BAVT), a