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Long-tail semantic failures in document understanding are exposed when models are forced to reason with a unified vocabulary of visual anchors rather than treating elements in isolation.
A2D2 achieves superior reward optimization and generation accuracy by seamlessly integrating insertion and unmasking strategies in discrete diffusion models.
The hardest AI tasks remain largely unsolved, with current models achieving only a 2.6% success rate on economically valuable workflows.