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Misbinding errors in vision-language models can hide behind high aggregate accuracy, with open-source models misassigning attributes 19.84% of the time.
Exact boundary enforcement in PINNs isn't enough; the choice of distance function can make or break the accuracy of solutions to elliptic Dirichlet problems.
