GPA: Learning GUI Process Automation from Demonstrations

📰 ArXiv cs.AI

GPA learns GUI process automation from demonstrations using vision-based Robotic Process Automation

advanced Published 7 Apr 2026
Action Steps
  1. Collect demonstration data of GUI interactions
  2. Apply Sequential Monte Carlo-based localization for robust detection and handling of rescaling and uncertainty
  3. Implement vision-based Robotic Process Automation for process replay
  4. Refine and optimize GPA model for improved performance and accuracy
Who Needs to Know This

AI engineers and software engineers on a team can benefit from GPA as it enables fast and stable process replay with minimal demonstrations, improving automation efficiency and reducing errors

Key Insight

💡 GPA introduces robustness via Sequential Monte Carlo-based localization for vision-based GUI automation

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🤖 Learn GUI automation from demos with GPA!
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