2026
SPICE: Submodular Penalized Information–Conflict Selection for Efficient Large Language Model Training
ICLR 2026poster
Information-based data selection for instruction tuning is compelling: maximizing the log-determinant of the Fisher information yields a monotone submodular objective, enabling greedy algorithms to achieve a $(1-1/e)$ approximation under a cardinality budget. In practice, however, we identify allevi…