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.

公开(公告)号：US12175197B2

公开(公告)日：2024-12-24

申请号：US17778628

申请日：2019-11-21

Applicant: Google LLC

Inventor： Simon Baumgartner ,  Shan Jiang ,  Abraham P. Ittycheriah ,  Cong Yu

IPC: G06F40/30 ,  G06F40/279

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate automatic identification of a set of fact-check factors from digital documents. Digital documents can be identified from a plurality of sources. For each digital document, a set of fact check factors are identified using a trained sequence tagging model. Based on the sequence tagging model, a confidence value representing a likelihood that the set of fact check factors identified from the digital document are an actual set of fact check factors for the digital document is determined. The set of fact check factors is stored in association with the digital document. A request for fact check factors for a particular digital document among the digital documents is received from a fact checking entity. In response, the set of fact check factors identified from the particular digital document are provided to the fact checking entity.

公开(公告)号：US20220335221A1

公开(公告)日：2022-10-20

申请号：US17778628

申请日：2019-11-21

Applicant: Google LLC

Inventor： Simon Baumgartner ,  Shan Jiang ,  Abraham P. Ittycheriah ,  Cong Yu

IPC: G06F40/30 ,  G06F40/279

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate automatic log identification of a set of fact-check factors from digital documents. Digital documents can be identified from a plurality of sources. For each digital document, a set of fact check factors are identified using a trained sequence Fact Checking tagging model. Based on the sequence tagging model, a confidence value representing a likelihood that the set of fact check factors identified from the digital document are an actual set of fact check factors for the digital document is determined. The set of fact check factors is stored in association with the digital document. A request for fact check factors for a particular digital document among the digital documents is received from a fact checking entity. In response, the set of fact check factors identified from the particular digital document are provided to the fact checking entity.