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cs.LG2025
CLID-MU: Cross-Layer Information Divergence Based Meta Update Strategy for Learning with Noisy Labels
Ruofan Hu, Dongyu Zhang, Huayi Zhang +1
Learning with noisy labels (LNL) is essential for training deep neural networks with imperfect data. Meta-learning approaches have achieved success by using a clean unbiased labele…
cs.LG2024
ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning
Yang Wu, Huayi Zhang, Yizheng Jiao +6
Instruction tuning has underscored the significant potential of large language models (LLMs) in producing more human controllable and effective outputs in various domains. In this…