GUI Agent

https://chat.fellou.ai/report/306a99a6-5c4b-4323-be49-c0d43cf837f8

(한국어번역본)

Fellou

 

https://chat.fellou.ai/report/8e599da3-b0f8-48da-8a8c-7b79cdd5a20b

(영어원문)

Fellou

 

Article Review Template

Summary

• This report summarizes ten research papers focused on GUI Agents, exploring their development, evaluation, and application in various environments. The papers cover topics such as GUI agent architectures, training methods, benchmarks, and the integration of large language models (LLMs) for enhanced interaction capabilities.

Key Points

1. GUI Agents: A Survey - Provides a comprehensive overview of GUI agents, discussing benchmarks, architectures, and training methods. Highlights the challenges and future directions in GUI agent research.
2. Large Language Model-Brained GUI Agents - Explores the integration of LLMs in GUI agents, enabling complex task execution through natural language commands.
3. Graphical User Interface Agents Optimization - Focuses on optimizing GUI agents for visual instruction grounding using multi-modal AI systems.
4. Autonomous GUI Testing using Deep Reinforcement Learning - Introduces a novel approach for automating GUI testing, enhancing coverage and efficiency.
5. CogAgent: A Visual Language Model for GUI Agents - Describes a visual language model designed for GUI understanding and navigation, outperforming traditional methods.
6. Agent based graphical user interface architecture - Discusses a flexible GUI software model for consumer products using an agent-based paradigm.
7. AssistEditor: Multi-Agent Collaboration for GUI Workflow Automation - Examines the use of multi-agent systems for automating GUI workflows in video creation.
8. Automated Power-saving User-interfaces - Investigates power-saving strategies in GUI design, focusing on energy efficiency in mobile applications.
9. Agent. GUI: A multi-agent based simulation framework - Explores the use of multi-agent systems in simulation frameworks, highlighting their benefits in various applications.
10. GUI for the communication agent of the “Nephele” data center - Presents a GUI for managing communication agents in data centers, emphasizing its role in testing and monitoring.

Questions

• How do GUI agents handle dynamic changes in web environments?
• What are the limitations of current LLM integrations in GUI agents?
• How can GUI agents be further optimized for real-time applications?

References

• Nguyen, D., et al. (2024). GUI Agents: A Survey. arXiv.
• Zhang, C., et al. (2024). Large Language Model-Brained GUI Agents: A Survey. arXiv.
• Dardouri, T., et al. (2024). Graphical user interface agents optimization for visual instruction grounding. arXiv.
• Authors. (2021). Autonomous GUI Testing using Deep Reinforcement Learning. IEEE.
• Authors. (2024). CogAgent: A Visual Language Model for GUI Agents. IEEE.
• Authors. (1996). Agent based graphical user interface architecture for consumer products. IEEE.
• Gao, D., et al. (2024). AssistEditor: Multi-Agent Collaboration for GUI Workflow Automation. ACM.
• Yeh, H.-C., et al. (2025). Automated Power-saving User-interfaces for Application Designers. ACM.
• Authors. (2020). Agent. GUI: A multi-agent based simulation framework. IEEE.
• Authors. (2024). GUI for the communication agent of the “Nephele” data center. IEEE.