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Visual Quality Assurance Using Vision-Language Models – Cor-Paul Bezemer
Session Outline:
Why Visual QA Matters – Ensuring user trust and correctness in dynamic, visual interfaces.
Limits of Manual and Snapshot Testing – Current methods are brittle and labor-intensive.
Non-Determinism in Modern Software – AI-driven behavior makes pixel-perfect matching unreliable.
When Bugs Aren’t Bugs – Why visual differences don’t always indicate regressions.
The Commonsense Gap – Many visual issues require human-like reasoning.
Vision-Language Models for Visual QA – Using multimodal models to understand and evaluate visual intent.
Detecting Subtle Visual Failures – Identifying layout, style, and semantic inconsistencies.
Natural Language Explanations – Producing interpretable reports for visual issues.
Challenges and Open Questions – Hallucinations, evaluation criteria, and integration hurdles.
Toward Smarter Testing Pipelines – Embedding VLMs into scalable, automated QA workflows.
