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Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents
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tool-usevalue estimationcomparative inferencelong-horizon decision-making
2610.02330
Builder Relevance
1h ago80%
Abstract
This paper discusses the importance of estimating the long-horizon value of tool invocations in large language models to improve task success.
Reality Card
Core Claim
The proposed Comparative Inference for Tool-use Agents (CITA) significantly enhances tool-use performance by accurately estimating the value of potential tool invocations.
Method / Result
CITA consistently improves Tool F1 and task success across three benchmarks.
Limitations
The method relies on paired signals and may require complex setups for effective implementation.
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