Emergence WebVoyager: Toward Consistent and Transparent Evaluation of (Web) Agents in The Wild
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 introduce Emergence WebVoyager, an enhanced version of the WebVoyager benchmark that standardizes evaluation methodology through clear guidelines for t...
| Authors | Deepak Akkil, Mowafak Allaham, Amal Raj et al. |
|---|---|
| Primary category | cs.AI |
| Published | 30 March 2026 |
| Last updated at source | 30 March 2026 |
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