A study submitted to arXiv on November 12, 2026, by researchers at Cornell University and Howard Hughes Medical Institute introduces AgentSSL, the first systematic framework evaluating how autonomous machine learning engineering agents leverage unlabeled data in semi-supervised workflows.
