让数据分析智能体像人类一样有条理地思考，提升洞察力准确性。
I2I-STRADA -- Information to Insights via Structured Reasoning Agent for Data Analysis
- 设计模块化推理流程，模拟人类分析的完整思维链
- 在DABstep和DABench上优于现有系统，规划更连贯、洞察更对齐
- 适合需要可解释、稳定分析结果的研究者与企业用户
近期数据分析师智能体研究强调通过多智能体框架和编排层实现洞察自动生成。尽管这些系统能有效处理查询转换、数据变换和可视化任务，却常忽视分析思维背后的结构化推理过程。用于多步问题求解的大型语言模型（LLMs）作为通用求解器进行训练，其推理步骤缺乏特定任务的固定流程。真实世界的数据分析需要一致的认知工作流：理解模糊目标、基于上下文知识定位问题、构建抽象计划，并根据中间结果调整执行。我们提出I2I-STRADA（Information-to-Insight via Structured Reasoning Agent for Data Analysis），一种旨在形式化该推理过程的智能体架构。I2I-STRADA通过反映分析性推理认知步骤的模块化子任务来建模分析过程。在DABstep和DABench基准上的评估显示，I2I-STRADA在规划连贯性和洞察对齐性方面优于先前系统，凸显了结构化认知工作流在数据解析智能体设计中的重要性。
原文摘要 · Abstract (English)
Recent advances in agentic systems for data analysis have emphasized automation of insight generation through multi-agent frameworks, and orchestration layers. While these systems effectively manage tasks like query translation, data transformation, and visualization, they often overlook the structured reasoning process underlying analytical thinking. Reasoning large language models (LLMs) used for multi-step problem solving are trained as general-purpose problem solvers. As a result, their reasoning or thinking steps do not adhere to fixed processes for specific tasks. Real-world data analysis requires a consistent cognitive workflow: interpreting vague goals, grounding them in contextual knowledge, constructing abstract plans, and adapting execution based on intermediate outcomes. We introduce I2I-STRADA (Information-to-Insight via Structured Reasoning Agent for Data Analysis), an agentic architecture designed to formalize this reasoning process. I2I-STRADA focuses on modeling how analysis unfolds via modular sub-tasks that reflect the cognitive steps of analytical reasoning. Evaluations on the DABstep and DABench benchmarks show that I2I-STRADA outperforms prior systems in planning coherence and insight alignment, highlighting the importance of structured cognitive workflows in agent design for data analysis.
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