The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 07, 2026

Filed:

Sep. 01, 2023
Applicant:

Salesforce, Inc., San Francisco, CA (US);

Inventors:

Philippe Laban, New York, NY (US);

Jesse Vig, Los Altos, CA (US);

Wojciech Kryscinski, Palo Alto, CA (US);

Assignee:

Salesforce, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/27 (2006.01); G06F 40/166 (2020.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01); G06F 40/40 (2020.01);
U.S. Cl.
CPC ...
G06F 40/40 (2020.01); G06F 40/166 (2020.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01);
Abstract

A method of training a text simplification model is provided. A training dataset including a first set of original textual samples and original revision histories and a second set of simplified textual samples and simplified revision histories is received via a data interface. A training pair including an original textual sample and corresponding original revision history from the first set and a counterpart simplified textual sample and corresponding simplified revision history from the second set are identified. An alignment label for a first revision in the corresponding original revision history and a second revision in the corresponding simplified revision history are generated using a neural network-based alignment model from a score. A revision category label for each of the first revision and second revision is generated using a neural network-based classification model. A neural network-based text simplification model is trained based on the updated training dataset.


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