arXiv Machine Learning By Wei Tang, Yin-Fang Yang, Weijia Zhang, Min-Ling Zhang

Calibratable Disambiguation Loss for Multi-Instance Partial-Label Learning

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arXiv:2512. 17788v2 Announce Type: replace Abstract: Multi-instance partial-label learning (MIPL) is a weakly supervised framework that extends the principles of multi-instance learning (MIL) and partial-label learning (PLL) to address the challenges of inexact supervision in both instance and label spaces.

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