OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization

OpenWebVoyager is a multimodal web agent that improves itself through repeated cycles of real-world exploration, feedback collection, and policy optimization. It starts from imitation learning, mines open-web trajectories, and shows stronger performance after each optimization round.

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  October 12, 2026 · arXiv
• SCAFFOLD: Self-Improving Web Agents via Recursive Parametric Skill Abstraction
  August 31, 2026 · arXiv
• Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction
  June 9, 2025 · SEA @ NeurIPS 2025 (Oral)
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• Large Language Models Can Self-Improve At Web Agent Tasks
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• Learning What to Ask for Tomorrow: Active Preference Acquisition for Long-Term Personalized Web Agents
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• Step-Aligned Script Generation with Verification and Recovery for Web Automation Testing
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