BEAP-Agent: Backtrackable Execution and Adaptive Planning for GUI Agents
On the map: LLM agents and tool use → GUI and mobile agents
Abstract (arXiv)
GUI agents are designed to automate repetitive tasks and enhance productivity. However, existing GUI agents struggle to recover once they follow an incorrect exploration path, often leading to task failure. In this work, we model GUI task execution as a DFS process and propose BEAP-Agent, a DFS-based framework that supports long-range, multi-level state backtracking with dynamic task tracking and updating. The framework consists of three collaborative components: Planner, Executor, and Tracker. Together, they enable effective task exploration and execution. BEAP-Agent fills the gap in systematic backtracking mechanisms for GUI agents, offering a systematic solution for long-horizon task exploration. We conducted a systematic evaluation on the OSWorld benchmark, where BEAP-Agent achieved an accuracy of 28.2%, validating the effectiveness of the proposed method.
Key facts. Cited by 1 paper 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 21 of its 22 references that are in the map. First posted on arXiv 29 Jan 2026.
Builds on
21 of 22 references.
Closest ancestors · 12
Same direction, newest first
- 2025UI-AGILE: Advancing GUI Agents with Effective Reinforcement Learning and Precise Inference-Time Grounding29 Jul
- 2025BacktrackAgent: Enhancing GUI Agent with Error Detection and Backtracking Mechanism27 May
- 2025ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay22 May
- 2025Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis19 May
- 2025Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents1 Apr
- 2025UI-TARS: Pioneering Automated GUI Interaction with Native Agents21 Jan
- 2024GUI Agents: A Survey18 Dec
- 2024Large Language Model-Brained GUI Agents: A Survey27 Nov
- 2024OS-ATLAS: A Foundation Action Model for Generalist GUI Agents30 Oct
- 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments11 Apr
- 2024ScreenAgent: A Vision Language Model-driven Computer Control Agent9 Feb
- 2023CogAgent: A Visual Language Model for GUI Agents14 Dec
Other references · 9
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2025Qwen2.5-VL Technical Reportcited by 5,418
- 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
- 2024Aguvis: Unified Pure Vision Agents for Autonomous GUI Interactioncited by 271
- 2024UFO: A UI-Focused Agent for Windows OS Interactioncited by 147
- 2025GTA1: GUI Test-time Scaling Agentcited by 102
- 2024OmniParser: A Unified Framework for Text Spotting, Key Information Extraction and Table Recognitioncited by 74
- 2025UFO2: The Desktop AgentOScited by 38
- 2024OSCAR: Operating System Control via State-Aware Reasoning and Re-Planningcited by 37
Built on by
Citing papers per year: 2026: 1.
1 paper.
- 2026Signal-Driven Observation for Long-Horizon Web Agentscited by 0
- 2026Signal-Driven Observation for Long-Horizon Web Agents4 Jun 2026
Similar, not cited
Close in wording, no citation either way
- 2025Training High-Level Schedulers with Execution-Feedback Reinforcement Learning for Long-Horizon GUI Automation
- 2025ScaleTrack: Scaling and back-tracking Automated GUI Agents
- 2026Reflect, Revise, Reuse: Training-Free Skill Evolution for GUI Agents
- 2025MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents
- 2026WindowsWorld: A Process-Centric Benchmark of Autonomous GUI Agents in Professional Cross-Application Environments
- 2026Efficient GUI Agents: A Systems Survey of Observation, Memory, Action, and Runtime Optimization
- 2025WorldGUI: An Interactive Benchmark for Desktop GUI Automation from Any Starting Point
- 2026A Task-State Representation for Long-Horizon Mobile GUI Agents