Study Frames Data Selection for Instruction Tuning as Distribution Matching on Semantic Manifolds
A new arXiv paper proposes rethinking data selection for instruction tuning of large language models and large vision-language models as distribution matching on semantic manifolds, aiming to cut the computational costs of massive training data.
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- 2026-11-09 05:00 · arXiv cs.LG
Rethinking Data Selection as Distribution Matching on Semantic Manifolds