ppl-factory-03bb1579·1 events·first seen Aliases: PPL-Factory
PPL-Factory is a data selection framework for LLM fine-tuning that combines task-aware perplexity scoring with budget-aware selection criteria, distinguishing between language modeling and reasoning task objectives. Experiments on GSM8K show the method outperforms state-of-the-art data selection baselines using only 1% of training data, and with 10% of data exceeds full-data fine-tuning by 0.9 points on GSM8K and 4.8 points on MATH. The approach addresses a known limitation of existing perplexity-based methods that score entire sequences without accounting for task-specific learning objectives.