EFFICIENT LLMS WITH SPECULATIVE DECODING

Summary from the TLDR AI newsletter

Researchers have tackled the efficiency issues in autoregressive large language models by exploring linear attention methods combined with speculative decoding. This study introduces an augmentation technique for linear attention, making it compatible with speculative decoding and improving both training and performance.