Weblica: Scalable and Reproducible Training Environments for Visual Web Agents

• URL: http://arxiv.org/abs/2605.06761v1
• Date: Thu, 07 May 2026 17:17:10 GMT
• Title: Weblica: Scalable and Reproducible Training Environments for Visual Web Agents
• Abstract summary: Weblica is a framework for constructing reproducible and scalable web environments.<n>We scale RL training to thousands of diverse environments and tasks.<n>Our best model, Weblica-8B, outperforms open-weight baselines of similar size across multiple web navigation benchmarks.
• Score: 5.132610127852326
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The web is complex, open-ended, and constantly changing, making it challenging to scale training data for visual web agents. Existing data collection attempts remain limited to offline trajectories for supervised fine-tuning or a handful of simulated environments for RL training, thus failing to capture web diversity. We propose Weblica (Web Replica), a framework for constructing reproducible and scalable web environments. Our framework leverages 1) HTTP-level caching to capture and replay stable visual states while preserving interactive behavior and 2) LLM-based environment synthesis grounded in real-world websites and core web navigation skills. Using this framework, we scale RL training to thousands of diverse environments and tasks. Our best model, Weblica-8B, outperforms open-weight baselines of similar size across multiple web navigation benchmarks while using fewer inference steps, scales favorably with additional test-time compute, and is competitive with API models.

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