mlsanityData to 7 Oct 2026

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

arXiv 2602.10814 ↗First posted 11 Feb 2026cs.AIcited by 0

On the map: LLM agents and tool use → GUI and mobile agents

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in GUI and mobile agents, one of 16 directions in LLM agents and tool use. Builds on 28 of its 56 references that are in the map. First posted on arXiv 11 Feb 2026.

Builds on

28 of 56 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents1 Apr
  2. 2025UI-TARS: Pioneering Automated GUI Interaction with Native Agents21 Jan
  3. 2024Agent S: An Open Agentic Framework that Uses Computers Like a Human10 Oct
  4. 2024On the Effects of Data Scale on UI Control Agents6 Jun
  5. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments11 Apr
  6. 2024OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web27 Feb

Other references · 22

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2021Program Synthesis with Large Language Modelscited by 3,509
  3. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  4. 2023Code Llama: Open Foundation Models for Codecited by 2,105
  5. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
  6. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,628
  7. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,210
  8. 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,197
  9. 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agentscited by 956
  10. 2025DeepSeek-V3.2: Pushing the Frontier of Open Large Language Modelscited by 755
  11. 2024AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agentscited by 450
  12. 2024DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligencecited by 325
10 more
  1. 2023CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-Xcited by 294
  2. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challengescited by 278
  3. 2023Is Self-Repair a Silver Bullet for Code Generation?cited by 191
  4. 2025PaddleOCR 3.0 Technical Reportcited by 136
  5. 2025UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interactioncited by 68
  6. 2025PatchPilot: A Cost-Efficient Software Engineering Agent with Early Attempts on Formal Verificationcited by 22
  7. 2024CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technologycited by 21
  8. 2025Scratch Copilot: Supporting Youth Creative Coding with AIcited by 3
  9. 2025LitterBox+: An Extensible Framework for LLM-enhanced Scratch Static Code Analysiscited by 2
  10. 2025Stitch: Step-by-step LLM Guided Tutoring for Scratchcited by 2

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Not cited yet.

Similar, not cited

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