AI RESEARCH
Emergence WebVoyager: Toward Consistent and Transparent Evaluation of (Web) Agents in The Wild
arXiv CS.AI
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ArXi:2603.29020v1 Announce Type: new Reliable evaluation of AI agents operating in complex, real-world environments requires methodologies that are robust, transparent, and contextually aligned with the tasks agents are intended to perform. This study identifies persistent shortcomings in existing AI agent evaluation practices that are particularly acute in web agent evaluation, as exemplified by our audit of WebVoyager, including task-framing ambiguity and operational variability that hinder meaningful and reproducible performance comparisons. To address these challenges, we.