High-Value Training Data from Noisy, Diverse Sources.

arXiv:2610.30421v1 Announce Type: cross 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 differen