Beyond ReAct: A Planner-Centric Framework for Complex Tool-Augmented LLM Reasoning

• URL: http://arxiv.org/abs/2511.10037v1
• Date: Fri, 14 Nov 2025 01:27:38 GMT
• Title: Beyond ReAct: A Planner-Centric Framework for Complex Tool-Augmented LLM Reasoning
• Authors: Xiaolong Wei, Yuehu Dong, Xingliang Wang, Xingyu Zhang, Zhejun Zhao, Dongdong Shen, Long Xia, Dawei Yin,
• Abstract summary: We propose a Planner-centric Plan-Execute paradigm to resolve local optimization bottlenecks.<n>A novel Planner model performs global Directed Acyclic Graph (DAG) planning for complex queries.<n>We also introduce ComplexTool-Plan, a large-scale benchmark dataset featuring complex queries.<n>When integrated with a capable executor, our framework achieves state-of-the-art performance on the StableToolBench benchmark for complex user queries.
• Score: 31.679428422518082
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Existing tool-augmented large language models (LLMs) encounter significant challenges when processing complex queries. Current frameworks such as ReAct are prone to local optimization traps due to their reliance on incremental decision-making processes. To address these limitations, we propose a novel Planner-centric Plan-Execute paradigm that fundamentally resolves local optimization bottlenecks through architectural innovation. Central to our approach is a novel Planner model that performs global Directed Acyclic Graph (DAG) planning for complex queries, enabling optimized execution beyond conventional tool coordination. We also introduce ComplexTool-Plan, a large-scale benchmark dataset featuring complex queries that demand sophisticated multi-tool composition and coordination capabilities. Additionally, we develop a two-stage training methodology that integrates Supervised Fine-Tuning (SFT) with Group Relative Policy Optimization (GRPO), systematically enhancing the Planner's tool selection accuracy and global planning awareness through structured DAG-based planning. When integrated with a capable executor, our framework achieves state-of-the-art performance on the StableToolBench benchmark for complex user queries, demonstrating superior end-to-end execution capabilities and robust handling of intricate multi-tool workflows.

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