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Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning.

arXiv:2507.12612v5 Announce Type: replace-cross Abstract: Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set of tasks. In practice, mixtures are often fixed using simpl

arXiv cs.AIResearch source·