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MLLMs exhibit a staggering 80.22% bias towards incorrect outputs when faced with repeated UI patterns, revealing a critical flaw in their code generation capabilities.
AI-generated code lacks transparency, but a new framework for automated provenance could revolutionize developer trust and compliance.
Software engineers need more than just coding skills in the age of GenAI: prompting, critical thinking, and architecture design are now crucial for bridging the gap between academia and industry.
