Influence Matching aligns synthetic datasets with final converged parameters

Influence Matching (Inf-Match) performs dataset distillation by aligning the final outcome of training rather than intermediate gradients. It uses a differentiable, linear-time sample-level influence estimator based on first-order Taylor approximations to create compact synthetic sets that match the parameter shifts of full datasets.