Visual Regression Agent Benchmark
Transparent methodology for measuring governed agent fleets. Results published as available, framework pages labeled clearly when data is in progress. This page documents methodology; results are published when available.
What is measured
Precision and recall of visual change detection with human-labeled ground truth across UI surfaces.
Visual validation must minimize false positives that block releases while catching real regressions.
Methodology
Labeled screenshot pairs across design systems and dynamic content. Agents run with consistent viewport and timing; judges score true positive, false positive, and missed regression.
Limitations
Dataset scope is finite; dynamic ads and third-party embeds may behave differently in your environment.
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Transparent methodology for measuring governed agent fleets. Results published as available, framework pages labeled clearly when data is in progress.
