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NaviAgent improves LLM tool orchestration with bilevel planning

By PulseAugur Editorial · [1 sources] ·

Researchers have developed NaviAgent, a novel system designed to improve how large language models orchestrate the use of external tools. NaviAgent employs a bilevel architecture that separates task planning from tool execution, using graph-based modeling to understand the relationships between hundreds or thousands of tools. This approach aims to reduce errors and enhance scalability by allowing agents to plan toolchains independently of inter-tool complexity. Evaluations on benchmarks like API-Bank and ToolBench demonstrated significant improvements in task success rates, particularly for complex tasks. AI

IMPACT Enhances LLM capabilities for complex, multi-tool tasks, potentially improving agent performance and scalability.

RANK_REASON The cluster contains an arXiv paper detailing a new method for LLM tool orchestration. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NaviAgent improves LLM tool orchestration with bilevel planning

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The cluster contains an arXiv paper detailing a new method for LLM tool orchestration. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yan Jiang, Hao Zhou, Lizhong GU, Tianlong Li, Ruinan Jin, Wanqi Zhou, Ai Han ·

    NaviAgent: Graph-Driven Bilevel Planning for Scalable Tool Orchestration

    arXiv:2506.19500v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge. However, they typically invoke tools one at a time without a global view of ta…

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