Prototypes, Not Guesswork: Rethinking Trust in Multi‑View Classification
Pizza. The image says pizza. The text description says baklava. A human sees the contradiction immediately. A multi-view classifier may not. It may average the views, let one noisy modality dominate, or produce a confident answer from evidence that should have triggered suspicion. Very impressive, in the same way a committee can be impressive while approving the wrong invoice. ...