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Current Vision-Language Models struggle with engineering reasoning, revealing critical gaps in their ability to interpret technical diagrams and apply physical principles.
VLMs hallucinate less when you force them to "think twice" by contrasting language-driven and vision-driven token probabilities at each decoding step.
