Do GUI Agents Believe Their Eyes? Diagnosing State-Belief Reliance on Pixels versus Structure
arXiv:2607.04334v1 Announce Type: new Abstract: Multimodal GUI agents read an interface through two redundant channels: the rendered pixels of a screenshot and a serialized structure such as a DOM or accessibility tree. Before acting, an agent forms a belief about the current interface state, but existing benchmarks score task success, element grounding, or attack resistance and do not ask whether that belief is drawn from the pixels. We formalize visual state reliance, the attribution of a state belief to pixels, structure, or priors, and measure it with paired single-channel interventions ov
The proliferation of multimodal AI agents necessitates a deeper understanding of their perceptual mechanisms, moving beyond simple task success metrics.
Understanding how GUI agents form beliefs about interface states is crucial for building more robust, reliable, and interpretable AI systems, especially for critical applications.
The formalization of 'visual state reliance' and methods for measuring it provides a new diagnostic tool for evaluating AI agent cognition beyond just performance outcomes.
- · AI agent developers
- · AI safety researchers
- · UX designers for AI-driven interfaces
- · Software testing industry
- · Developers of opaque AI systems
- · Traditional GUI testing methodologies
Improved debugging and interpretability of multimodal AI agents interacting with graphical user interfaces.
Development of more resilient AI agents that are less susceptible to adversarial attacks exploiting pixel-level vulnerabilities.
New benchmarks and certifications for AI agent reliability based on their state-belief formation processes.
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Read at arXiv cs.AI