Nonparametric Teaching of Attention Learners

A new teaching paradigm called Attention Neural Teaching (AtteNT) has been introduced to improve the efficiency of training attention-based neural networks like transformers without sacrificing accuracy. This method accelerates convergence by selecting key sequence-property pairs for training, resulting in significant time reductions for both large language models and vision transformers while maintaining or enhancing performance.

Read the full article at arXiv cs.LG (ML)

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