WebChallenger: A Reliable and Efficient Generalist Web Agent

WebChallenger addresses autonomous web navigation by encoding three architectural components — selective DOM-based attention via PageMem, persistent site-structure memory, and procedural interaction patterns — rather than scaling model size. The framework targets the cost gap between proprietary reasoning models and practical deployment, arguing current agent failures are architectural, not capability-limited.