EcomBench：电商领域基础智能体的整体性评估框架

摘要

基础智能体在现实环境中的推理与交互能力迅速发展，使其核心能力的评估变得日益重要。尽管现有评估基准层出不穷，但大多聚焦于学术场景或人工设计的情境，忽视了真实应用中的挑战。针对这一问题，我们着眼于极具现实意义的电商领域——该领域涉及海量多元用户交互、动态市场环境，以及与现实决策流程直接关联的任务。为此，我们推出EcomBench：一个旨在真实电商环境中评估智能体性能的综合性基准。该基准源自全球头部电商生态中的真实用户需求，经由专家人工标注与校验，确保任务清晰度、准确性与领域相关性。它覆盖电商场景下的多类任务，设定了三个难度层级，重点考察智能体的深层信息检索、多步推理及跨源知识整合等关键能力。通过将评估植根于真实电商语境，EcomBench为衡量智能体在现代电商场景中的实际能力提供了严谨而动态的测试平台。

English

Foundation agents have rapidly advanced in their ability to reason and interact with real environments, making the evaluation of their core capabilities increasingly important. While many benchmarks have been developed to assess agent performance, most concentrate on academic settings or artificially designed scenarios while overlooking the challenges that arise in real applications. To address this issue, we focus on a highly practical real-world setting, the e-commerce domain, which involves a large volume of diverse user interactions, dynamic market conditions, and tasks directly tied to real decision-making processes. To this end, we introduce EcomBench, a holistic E-commerce Benchmark designed to evaluate agent performance in realistic e-commerce environments. EcomBench is built from genuine user demands embedded in leading global e-commerce ecosystems and is carefully curated and annotated through human experts to ensure clarity, accuracy, and domain relevance. It covers multiple task categories within e-commerce scenarios and defines three difficulty levels that evaluate agents on key capabilities such as deep information retrieval, multi-step reasoning, and cross-source knowledge integration. By grounding evaluation in real e-commerce contexts, EcomBench provides a rigorous and dynamic testbed for measuring the practical capabilities of agents in modern e-commerce.

EcomBench：电商领域基础智能体的整体性评估框架

EcomBench: Towards Holistic Evaluation of Foundation Agents in E-commerce

摘要

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