Core Concepts
Large language models (LLMs) can be significantly improved in their ability to leverage external tools for complex, multi-step tasks by using a novel step-grained reinforcement learning framework called StepTool.
Yu, Y., Wang, Z., Ma, W., Guo, Z., Zhan, J., Wang, S., Wu, C., Guo, Z., & Zhang, M. (2025). StepTool: A Step-grained Reinforcement Learning Framework for Tool Learning in LLMs. ICLR 2025 Conference Paper.
This paper addresses the limitations of existing tool learning methods for LLMs, which primarily rely on imitating expert trajectories and often result in suboptimal task-solving performance. The authors propose a novel step-grained reinforcement learning framework, StepTool, to enhance the ability of LLMs to effectively utilize external tools for complex, multi-step tasks.