mlsanityData to 7 Oct 2026

ProBench: Benchmarking GUI Agents with Accurate Process Information

arXiv 2511.09157 ↗First posted 12 Nov 2025cs.AIcited by 14

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

Abstract (arXiv)

With the deep integration of artificial intelligence and interactive technology, Graphical User Interface (GUI) Agent, as the carrier connecting goal-oriented natural language and real-world devices, has received widespread attention from the community. Contemporary benchmarks aim to evaluate the comprehensive capabilities of GUI agents in GUI operation tasks, generally determining task completion solely by inspecting the final screen state. However, GUI operation tasks consist of multiple chained steps while not all critical information is presented in the final few pages. Although a few research has begun to incorporate intermediate steps into evaluation, accurately and automatically capturing this process information still remains an open challenge. To address this weakness, we introduce ProBench, a comprehensive mobile benchmark with over 200 challenging GUI tasks covering widely-used scenarios. Remaining the traditional State-related Task evaluation, we extend our dataset to include Process-related Task and design a specialized evaluation method. A newly introduced Process Provider automatically supplies accurate process information, enabling presice assessment of agent's performance. Our evaluation of advanced GUI agents reveals significant limitations for real-world GUI scenarios. These shortcomings are prevalent across diverse models, including both large-scale generalist models and smaller, GUI-specific models. A detailed error analysis further exposes several universal problems, outlining concrete directions for future improvements.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Placed in GUI and mobile agents, one of 16 directions in LLM agents and tool use. Builds on 20 of its 34 references that are in the map. First posted on arXiv 12 Nov 2025.

Builds on

20 of 34 references.

Closest ancestors · 8

Same direction, newest first

  1. 2025GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents14 Apr
  2. 2025UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning27 Mar
  3. 2025UI-TARS: Pioneering Automated GUI Interaction with Native Agents21 Jan
  4. 2025A3: Android Agent Arena for Mobile GUI Agents with Essential-State Procedural Evaluation2 Jan
  5. 2024AndroidLab: Training and Systematic Benchmarking of Android Autonomous Agents31 Oct
  6. 2024OS-ATLAS: A Foundation Action Model for Generalist GUI Agents30 Oct
  7. 2024Benchmarking Mobile Device Control Agents across Diverse Configurations25 Apr
  8. 2024Android in the Zoo: Chain-of-Action-Thought for GUI Agents5 Mar

Other references · 12

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2025Qwen3 Technical Reportcited by 8,195
  3. 2025Qwen2.5-VL Technical Reportcited by 5,418
  4. 2024GPT-4o System Cardcited by 4,467
  5. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
  6. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,655
  7. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,769
  8. 2024MiniCPM-V: A GPT-4V Level MLLM on Your Phonecited by 1,061
  9. 2024AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agentscited by 450
  10. 2023Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4Vcited by 291
  11. 2022ScreenQA: Large-Scale Question-Answer Pairs over Mobile App Screenshotscited by 65
  12. 2022UGIF: UI Grounded Instruction Followingcited by 25

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 13.

14 papers.

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  1. 2025MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents
  2. 2026Beyond Sequential Interaction: Benchmarking Parallel Execution and Coordination for GUI Agents
  3. 2025WorldGUI: An Interactive Benchmark for Desktop GUI Automation from Any Starting Point
  4. 2026MobileBench-OL: A Comprehensive Chinese Benchmark for Evaluating Mobile GUI Agents in Real-World Environment
  5. 2025XBOUND: Exploring Capability Boundaries of Device-Control Agents at the State Level
  6. 2026JarvisGUI: Towards Cross-Device GUI Agents with Dynamic Task Composition
  7. 2026VenusBench-Mobile: A Challenging and User-Centric Benchmark for Mobile GUI Agents with Capability Diagnostics
  8. 2025GUI-360^circ: A Comprehensive Dataset and Benchmark for Computer-Using Agents