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cs.LG2024
Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning
Congyu Qiao, Ning Xu, Yihao Hu +1
Instance-dependent Partial Label Learning (ID-PLL) aims to learn a multi-class predictive model given training instances annotated with candidate labels related to features, among…
cs.CL2024
Progressively Label Enhancement for Large Language Model Alignment
Biao Liu, Ning Xu, Xin Geng
Large Language Models (LLM) alignment aims to prevent models from producing content that misaligns with human expectations, which can lead to ethical and legal concerns. In the las…