SPICE: Submodular Penalized Information-Conflict Selection for Efficient Large Language Model Training
DGX agentarXiv:2601.23155v2 Announce Type: replace-cross Abstract: Information-based data selection for instruction tuning is compelling: maximizing the log-determinant of the Fisher information yields a monot