OrchDAG: Complex Tool Orchestration in Multi-Turn Interactions with Plan DAGs

Yifu Lu; Shengjie Liu; Li Dong

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arXiv · 2510.24663

OrchDAG: Complex Tool Orchestration in Multi-Turn Interactions with Plan DAGs

Yifu Lu·Shengjie Liu·Li Dong

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Abstract

Agentic tool use has gained traction with the rise of agentic tool calling, yet most existing work overlooks the complexity of multi-turn tool interactions. We introduce OrchDAG, a synthetic data generation pipeline that models tool execution as directed acyclic graphs (DAGs) with controllable complexity. Using this dataset, we benchmark model performance and propose a graph-based reward to enhance RLVR training. Experiments show that the dataset presents a challenging but solvable benchmark, and the proposed reward is effective when combined with GRPO-style algorithms, highlighting the importance of leveraging topological structure and data complexity in multi-turn tool use.

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Yifu Lu, Shengjie Liu, Li Dong. 2025-10-28. OrchDAG: Complex Tool Orchestration in Multi-Turn Interactions with Plan DAGs. https://arxiv.org/abs/2510.24663

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