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VLMs suffer from "digital agnosia," exhibiting a surprisingly sharp failure to transcribe even small color grids into matrices, revealing a critical gap between visual feature encoding and language generation.
Even the best LLMs struggle to maintain correct intermediate states when solving university-level STEM problems, often taking more steps than necessary and accumulating errors along the way.
