AI RESEARCH
LAF-Based Evaluation and UTTL-Based Learning Strategies with MIATTs
arXiv CS.LG
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ArXi:2604.20944v1 Announce Type: new In many real-world machine learning (ML) applications, the true target cannot be precisely defined due to ambiguity or subjectivity information. To address this challenge, under the assumption that the true target for a given ML task is not assumed to exist objectively in the real world, the EL-MIATTs (Evaluation and Learning with Multiple Inaccurate True Targets) framework has been proposed.