Gaze regularization aligns VLA attention with human visual patterns via KL divergence on patch distributions, yielding 4-12% gains on manipulation benchmarks.
VQA-MHUG: A gaze dataset to study multimodal neural attention in visual question answering
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Gaze-Regularized Vision-Language-Action Models for Robotic Manipulation
Gaze regularization aligns VLA attention with human visual patterns via KL divergence on patch distributions, yielding 4-12% gains on manipulation benchmarks.