AI RESEARCH
FinToolBench: Evaluating LLM Agents for Real-World Financial Tool Use
arXiv CS.AI
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ArXi:2603.08262v1 Announce Type: new The integration of Large Language Models (LLMs) into the financial domain is driving a paradigm shift from passive information retrieval to dynamic, agentic interaction. While general-purpose tool learning has witnessed a surge in benchmarks, the financial sector, characterized by high stakes, strict compliance, and rapid data volatility, remains critically underserved. Existing financial evaluations predominantly focus on static textual analysis or document-based QA, ignoring the complex reality of tool execution.