实体 MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

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RESEARCH · CL_15913 · May 5 · 04:00

Researchers explore weight decay, in-context learning, and acceleration for Transformer models

Researchers have developed several new methods to improve the efficiency and theoretical understanding of Transformer models. One paper provides a functional-analytic characterization of weight decay, demonstrating its …

Researchers explore weight decay, in-context learning, and acceleration for Transformer models