FACTORIZING TRANSFORMERS FOR LINEAR TIME INFERENCE

Summary from the TLDR AI newsletter

This paper introduces a new transformer design that achieves linear time complexity during inference by factorizing the attention mechanism, reducing computational costs while maintaining model performance.