AI Agents 相关度: 8/10

See, Plan, Snap: Evaluating Multimodal GUI Agents in Scratch

Xingyi Zhang, Yulei Ye, Kaifeng Huang, Wenhao Li, Xiangfeng Wang
arXiv: 2602.10814v1 发布: 2026-02-11 更新: 2026-02-11

AI 摘要

提出了 ScratchWorld 基准测试,评估多模态 GUI 智能体在 Scratch 编程环境中的能力。

主要贡献

  • 提出了 ScratchWorld 基准测试
  • 设计了两种交互模式(primitive mode和composite mode)
  • 提出了基于执行的评估协议

方法论

构建 ScratchWorld 基准,包含多种编程任务,使用不同交互模式,并基于程序执行结果评估智能体。

原文摘要

Block-based programming environments such as Scratch play a central role in low-code education, yet evaluating the capabilities of AI agents to construct programs through Graphical User Interfaces (GUIs) remains underexplored. We introduce ScratchWorld, a benchmark for evaluating multimodal GUI agents on program-by-construction tasks in Scratch. Grounded in the Use-Modify-Create pedagogical framework, ScratchWorld comprises 83 curated tasks spanning four distinct problem categories: Create, Debug, Extend, and Compute. To rigorously diagnose the source of agent failures, the benchmark employs two complementary interaction modes: primitive mode requires fine-grained drag-and-drop manipulation to directly assess visuomotor control, while composite mode uses high-level semantic APIs to disentangle program reasoning from GUI execution. To ensure reliable assessment, we propose an execution-based evaluation protocol that validates the functional correctness of the constructed Scratch programs through runtime tests within the browser environment. Extensive experiments across state-of-the-art multimodal language models and GUI agents reveal a substantial reasoning--acting gap, highlighting persistent challenges in fine-grained GUI manipulation despite strong planning capabilities.

标签

多模态学习 GUI Agent 编程教育 基准测试

arXiv 分类

cs.AI