公开(公告)号：US20240020516A1

公开(公告)日：2024-01-18

申请号：US18222395

申请日：2023-07-14

Applicant: Google LLC

Inventor： Tal Schuster ,  Adam Joshua Fisch ,  Jai Prakash Gupta ,  Mostafa Dehghani ,  Dara Bahri ,  Vinh Quoc Tran ,  Yi Tay ,  Donald Arthur Metzler, Jr.

IPC: G06N3/0455

CPC classification number: G06N3/0455

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output sequences using auto-regressive decoder neural networks. In particular, during generation, adaptive early exiting is used to reduce the time required to generate the output sequence.

公开(公告)号：US11886976B1

公开(公告)日：2024-01-30

申请号：US18222395

申请日：2023-07-14

Applicant: Google LLC

Inventor： Tal Schuster ,  Adam Joshua Fisch ,  Jai Prakash Gupta ,  Mostafa Dehghani ,  Dara Bahri ,  Vinh Quoc Tran ,  Yi Tay ,  Donald Arthur Metzler, Jr.

IPC: G06N3/0455

CPC classification number: G06N3/0455

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output sequences using auto-regressive decoder neural networks. In particular, during generation, adaptive early exiting is used to reduce the time required to generate the output sequence.

公开(公告)号：US20240289552A1

公开(公告)日：2024-08-29

申请号：US18564859

申请日：2022-05-27

Applicant: Google LLC

Inventor： Yi Tay ,  Dara Bahri ,  Donald Arthur Metzler, Jr. ,  Hyung Won Chung ,  Jai Prakash Gupta ,  Sebastian Nikolas Ruder ,  Simon Baumgartner ,  Vinh Quoc Tran ,  Zhen Qin

IPC: G06F40/284

CPC classification number: G06F40/284

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing a machine learning task on an input sequence of characters that has a respective character at each of a plurality of character positions to generate a network output. One of the systems includes a neural network configured to perform the machine learning task, the neural network comprising a gradient-based sub-word tokenizer and an output neural network. The gradient-based sub-word tokenizer is configured to apply a learned, i.e., flexible, sub-word tokenization strategy to the input sequence of characters to generate a sequence of latent sub-word representations. The output neural network is configured to process the latent sub-word representation to generate the network output for the task.