Frederick S Liu

US Patent:

20230112862, Apr 13, 2023

Filed:

Oct 5, 2022

Appl. No.:

17/960380

Inventors:

- Mountain View CA, US
Andreas Veit - New York NY, US
Ayan Chakrabarti - New York NY, US
Frederick Liu - Bellevue WA, US
Himanshu Jain - New York NY, US
Michal Lukasik - New York NY, US
Sanjiv Kumar - Jericho NY, US

International Classification:

G06N 3/04

Abstract:

Provided are systems and methods that improve the computational efficiency of Transformers or other attention-based neural networks or machine learning models by re-using a number of attention scores between layers and/or heads of the model. To reduce the computational cost of self-attention-based models while achieving comparable or even superior results, example aspects of the present disclosure propose a novel architecture that reuses attention scores computed in one layer in one or multiple subsequent layers.