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:
Jul. 28, 2026

Filed:

Nov. 08, 2023
Applicant:

Snap Inc., Santa Monica, CA (US);

Inventors:

Aliaksei Mikhailiuk, London, GB;

Sergey Smetanin, London, GB;

Pavel Savchenkov, London, GB;

Hee Hun Kim, Los Angeles, CA (US);

Tianxiang Gao, Bothell, WA (US);

Neha Yadav, Seattle, WA (US);

Bingqian Lu, Ontario, CA (US);

Emily Ann Claudet, London, GB;

Assignee:

Snap Inc., Santa Monica, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/16 (2006.01); G06F 40/30 (2020.01); G06V 30/148 (2022.01); H04L 51/02 (2022.01); H04L 51/063 (2022.01);
U.S. Cl.
CPC ...
H04L 51/02 (2013.01); G06F 40/30 (2020.01); G06V 30/153 (2022.01); H04L 51/063 (2013.01);
Abstract

A computer-implemented method and system for responding to user posts containing images with relevant image responses during conversation between a user and a chatbot. The system receives an image post from the user and generates a description of the image using an image-to-text model. User intent is determined based on the image and description. If responding with an image is appropriate based on the user intent, the system generates a prompt using the image description and passes it to a text generation model to create an image description and caption. The image description and caption are used to synthesize a new image. The resulting image and caption are packaged into a post that is provided as a response to the user. The system uses machine learning pipelines and models to analyze images, detect inappropriate content, classify user intent, generate text, and synthesize images.


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