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News/Rethinking Data Selection as Distribution Matching on Semantic Manifolds
arxiv
PublishedNovember 10, 2026 at 5:00 AM

Rethinking Data Selection as Distribution Matching on Semantic Manifolds

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arXiv:2611.08495v1 Announce Type: cross Abstract: Instruction tuning of large language models and large vision language models relies on massive training data, which incurs substantial computational and storage costs. Meanwhile, training data often contains redundancy, noise, and low quality samples

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