Useful to Whom? Sample Value Is Defined Only Relative to the Learner

Excerpt

arXiv:2610.00221v1 Announce Type: new Abstract: What kind of data does a model need in order to learn? Coreset selection makes this question concrete: under a budget, keep the samples most useful for training. Easy-first and geometric coverage criteria can win in different budget regimes, separated by a crossover boundary. We ask whether this boundary is fixed by the data or changes with the target learner. Controlled experiments freeze the selected subsets and manipulate only the training learn