Shiji Zhou

Achieving a 25% reduction in prediction error, MOSH-WM redefines the landscape of object-centric video forecasting by grounding state representations in visual support.

Gradient manipulation in multi-task learning can be significantly enhanced by recognizing the matrix structure of model parameters, leading to superior optimization outcomes.

Retrieval strategies validated on one model can lead to significant performance gains in another, but only after rigorous experimental validation—VERDI makes this possible.