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Models trained on VBVR-Pro not only excel in native visual reasoning tasks but also reveal critical insights into the effectiveness of different generative modalities.
Achieving similar performance to larger models with significantly less data and faster inference speeds could redefine efficiency benchmarks in foundation models.
A 1000x larger video reasoning dataset reveals early signs of emergent generalization, offering a new foundation for training and evaluating spatiotemporal AI.
