作者位次 #7/8ACL 2026Findings· Findings of ACL
T ool G rad: Efficient Tool-use Dataset Generation with Textual “Gradients”
Zhongyi Zhou · Kohei Uehara · Haoyu Zhang · Jingtao Zhou · Lin Gu · Ruofei Du · Zheng Xu · Tatsuya Harada
摘要
Prior work synthesizes tool-use LLM datasets by first generating a user query, followed by complex tool-use annotations like DFS. This inherently leads to inevitable annotation failures and low efficiency in data generation. We introduce ToolGrad, an agentic framework that inverts this paradigm....