AIBullisharXiv – CS AI · Mar 177/10
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AutoTool: Automatic Scaling of Tool-Use Capabilities in RL via Decoupled Entropy Constraints
Researchers introduce AutoTool, a new reinforcement learning approach that enables AI agents to automatically scale their reasoning capabilities for tool use. The method uses entropy-based optimization and supervised fine-tuning to help models efficiently determine appropriate thinking lengths for simple versus complex problems, achieving 9.8% accuracy improvements while reducing computational overhead by 81%.