Scalable, Transferable Meta-network for Data Selection Requires a Different Loss (and Why the Obvious Choice is Problematic)
This paper proposes Transferable Example Scoring and Selection (TESS), a scalable data-selection framework for training large language models. TESS uses a Pointwise Value Matching objective to improve transferability and generalization.
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