AI RESEARCH
Negative Ontology of True Target for Machine Learning: Towards Evaluation and Learning under Democratic Supervision
arXiv CS.LG
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ArXi:2604.24824v1 Announce Type: new This article philosophically examines how shifts in assumptions regarding the existence and non-existence of the true target (TT) give rise to new perspectives and insights for machine learning (ML)-based predictive modeling and, correspondingly, proposes a knowledge system for evaluation and learning under cratic Supervision.