公开(公告)号：US20250103822A1

公开(公告)日：2025-03-27

申请号：US18372462

申请日：2023-09-25

Applicant: Adobe Inc.

Inventor： Niranjan Kumbi ,  Sreekanth Reddy ,  Sumit Bhatia ,  Milan Aggarwal ,  Simra Shahid ,  Nikitha Srikanth ,  Camille Girabawe ,  Narayanan Seshadri

IPC: G06F40/35

Abstract: System and methods for generating, validating, and augmenting question-answer pairs using generative AI are provided. An online interaction server accesses a set of digital content available at a set of designated network locations. The online interaction server further trains a pre-trained large language model (LLM) using the set of digital content to obtain a customized LLM. The online interaction server generates a set of question-answer pairs based on the set of digital content using the customized LLM and validates the set of question-answer pairs by determining if an answer in a question-answer pair is derived from the set of digital content. The online interaction server also selects a digital asset to augment an answer in a validated question-answer pair based on a semantic similarity between the validated question-answer pair and the digital asset.

公开(公告)号：US11960520B2

公开(公告)日：2024-04-16

申请号：US17853141

申请日：2022-06-29

Applicant: Adobe Inc.

Inventor： Tanay Anand ,  Sumit Bhatia ,  Simra Shahid ,  Nikitha Srikanth ,  Nikaash Puri

IPC: G06F16/30 ,  G06F16/33 ,  G06F16/35 ,  G06F16/93 ,  G06F18/2133 ,  G06F18/2413 ,  G06F40/30

CPC classification number: G06F16/35 ,  G06F16/3347 ,  G06F16/93 ,  G06F18/2133 ,  G06F18/24147 ,  G06F40/30

Abstract: Some techniques described herein relate to generating a hierarchical topic model (HTM), which can be used to generate custom content. In one example, a method includes determining first-level topics in a topic hierarchy related to a corpus of documents. A first-level topic of the first-level topics includes multiple words. The multiple words are grouped into clusters based on word embeddings of the multiple words. The multiple words are then subdivided into second-level topics as subtopics of the first-level topic, such that the number of second-level topics equals the number of clusters. A document of the corpus of documents is assigned to the first-level topic and to a second-level topic of the second-level topics, and an indication is received of access by a user to the document. Custom content is generated for the user based on one or more other documents assigned to the first-level topic and the second-level topic.

公开(公告)号：US20240355020A1

公开(公告)日：2024-10-24

申请号：US18304534

申请日：2023-04-21

Applicant: Adobe Inc.

Inventor： Yaman Kumar ,  Somesh Singh ,  Seoyoung Park ,  Pranjal Prasoon ,  Nithyakala Sainath ,  Nisarg Shailesh Joshi ,  Nikitha Srikanth ,  Nikaash Puri ,  Milan Aggarwal ,  Jayakumar Subramanian ,  Ganesh Palwe ,  Balaji Krishnamurthy ,  Matthew William Rozen ,  Mihir Naware ,  Hyman Chung

IPC: G06T11/60 ,  G06N20/20

CPC classification number: G06T11/60 ,  G06N20/20

Abstract: In implementations of systems for digital content analysis, a computing device implements an analysis system to extract a first content component and a second content component from digital content to be analyzed based on content metrics. The analysis system generates first embeddings using a first machine learning model and second embedding using a second machine learning model. The first embeddings and the second embeddings are combined as concatenated embeddings. The analysis system generates an indication of a content metric for display in a user interface using a third machine learning model based on the concatenated embeddings.

公开(公告)号：US20240004912A1

公开(公告)日：2024-01-04

申请号：US17853141

申请日：2022-06-29

Applicant: Adobe Inc.

Inventor： Tanay Anand ,  Sumit Bhatia ,  Simra Shahid ,  Nikitha Srikanth ,  Nikaash Puri

IPC: G06F16/35 ,  G06K9/62 ,  G06F16/93 ,  G06F40/30 ,  G06F16/33

CPC classification number: G06F16/35 ,  G06K9/6239 ,  G06K9/6276 ,  G06F16/93 ,  G06F40/30 ,  G06F16/3347

Abstract: Some techniques described herein relate to generating a hierarchical topic model (HTM), which can be used to generate custom content. In one example, a method includes determining first-level topics in a topic hierarchy related to a corpus of documents. A first-level topic of the first-level topics includes multiple words. The multiple words are grouped into clusters based on word embeddings of the multiple words. The multiple words are then subdivided into second-level topics as subtopics of the first-level topic, such that the number of second-level topics equals the number of clusters. A document of the corpus of documents is assigned to the first-level topic and to a second-level topic of the second-level topics, and an indication is received of access by a user to the document. Custom content is generated for the user based on one or more other documents assigned to the first-level topic and the second-level topic.