High-Value Training Data from Noisy, Diverse Sources
arXiv:2610.30421v1 Announce Type: new Abstract: Training state-of-the-art models increasingly requires learning from large, heterogeneous datasets whose examples vary in quality, domain relevance, and source of supervision. Dataweighting---assigning different weights to training examples---offers a…
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- 2026-10-23 04:00 · arXiv stat.ML
High-Value Training Data from Noisy, Diverse Sources