An optimization-first analysis of why VGGT's simpler architecture produces more geometrically consistent 3D reconstructions from few images than its higher-capacity successors — examining training dynamics, basin formation, gradient alignment, and the cost of abandoning a shared backbone.
This is a summary from my understanding of reinforcement learning, based on the book Reinforcement Learning: An Introduction by Sutton and Barto, and supplemented with the YouTube series.