Sparse Planning in Visual World Models via Cost Gradients
COSTGRAD is a training-free method that selects important spatial tokens from visual world models for planning. It ranks tokens based on how much they affect the planning cost, rather than just prediction error. This selection process allows planners to achieve performance comparable to full-token methods while significantly speeding up environment planning, offering substantial computational gains.