RESEARCH

Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents

ArXiv cs.AI · Mon, 05 Oct 2026 04:00:00 GMT

arXiv:2610.02330v1 Announce Type: new Abstract: Large language models (LLMs) rely on long-horizon tool invocation sequences for complex tasks, where each invocation can alter the task state and condition subsequent decisions. In long-horizon tool use, final-outcome rewards provid

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