Patents by Inventor Simra Shahid

Simra Shahid has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250148192
    Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for efficiently generating alternative examples for content. In embodiments, a source example prompt is obtained at a large language model. The source example prompt includes text associated with a source content and an instruction to generate a source example from the text associated with the source content. Using the large language model, the source example that represents an entity and corresponding context from the text is generated. Thereafter, the source example and a set of user segments are provided as input into the large language model to generate alternative examples associated with the source content. Each alternative example corresponds to a user segment of the set of user segments. Based on a particular user segment associated with a user interested in the source content, an alternative example corresponding to the particular user segment is provided for display.
    Type: Application
    Filed: November 3, 2023
    Publication date: May 8, 2025
    Inventors: Simra SHAHID, Nikitha SRIKANTH, Surgan JANDAIL, Balaji KRISHNAMURTHY
  • Publication number: 20250103822
    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.
    Type: Application
    Filed: September 25, 2023
    Publication date: March 27, 2025
    Inventors: Niranjan Kumbi, Sreekanth Reddy, Sumit Bhatia, Milan Aggarwal, Simra Shahid, Nikitha Srikanth, Camille Girabawe, Narayanan Seshadri
  • Patent number: 12223002
    Abstract: A method of finding online relevant conversing posts, comprises receiving, by a web server serving an online forum, a query post from an inquirer using the online forum, computing a contextual similarity score between each conversing post of a set of conversing posts with a query post, wherein the contextual similarity score is computed between the body of each of conversing posts and of the query post, wherein N1 conversing posts with a highest contextual similarity score are selected; computing a fine grained similarity score between the subject of the query post and of each of the N1 conversing posts, wherein N2 conversing posts with a highest fine grained similarity score are selected; and boosting the fine grained similarity score of the N2 conversing posts based on relevance metrics, wherein N3 highest ranked conversing posts are selected as a list of conversing posts most relevant to the query post.
    Type: Grant
    Filed: November 10, 2021
    Date of Patent: February 11, 2025
    Assignee: ADOBE INC.
    Inventors: Pinkesh Badjatiya, Tanay Anand, Simra Shahid, Nikaash Puri, Milan Aggarwal, S Sejal Naidu, Sharat Chandra Racha
  • Patent number: 12190061
    Abstract: Systems and methods for topic modeling are described. The systems and methods include encoding words of a document using an embedding matrix to obtain word embeddings for the document. The words of the document comprise a subset of words in a vocabulary, and the embedding matrix is trained as part of a topic attention network based on a plurality of topics. The systems and methods further include encoding a topic-word distribution matrix using the embedding matrix to obtain a topic embedding matrix. The topic-word distribution matrix represents relationships between the plurality of topics and the words of the vocabulary. The systems and methods further include computing a topic context matrix based on the topic embedding matrix and the word embeddings and identifying a topic for the document based on the topic context matrix.
    Type: Grant
    Filed: December 17, 2021
    Date of Patent: January 7, 2025
    Assignee: ADOBE INC.
    Inventors: Shashank Shailabh, Madhur Panwar, Milan Aggarwal, Pinkesh Badjatiya, Simra Shahid, Nikaash Puri, S Sejal Naidu, Sharat Chandra Racha, Balaji Krishnamurthy, Ganesh Karbhari Palwe
  • Publication number: 20240289380
    Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for determining user affinities by tracking historical user interactions with tagged digital content and using the user affinities in content generation applications. Accordingly, the system may track user interactions with published digital content in order to generate user interaction reports whenever a user engages with the digital content. The system may aggregate the interaction reports to generate an affinity profile for a user or audience of users. A marketer may then generate digital content for a target user or audience of users and the system may process the digital content to generate a set of tags for the digital content. Based on the set of tags, the system may then evaluate the digital content in view of the affinity profile for the target user/audience to determine similarities or differences between the digital content and the affinity profile.
    Type: Application
    Filed: May 6, 2024
    Publication date: August 29, 2024
    Inventors: Yaman Kumar, Vinh Ngoc Khuc, Vijay Srivastava, Umang Moorarka, Sukriti Verma, Simra Shahid, Shirsh Bansal, Shankar Venkitachalam, Sean Steimer, Sandipan Karmakar, Nimish Srivastav, Nikaash Puri, Mihir Naware, Kunal Kumar Jain, Kumar Mrityunjay Singh, Hyman Chung, Horea Bacila, Florin Silviu Lordache, Deepak Pai, Balaji Krishnamurthy
  • Patent number: 12008033
    Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for determining user affinities by tracking historical user interactions with tagged digital content and using the user affinities in content generation applications. Accordingly, the system may track user interactions with published digital content in order to generate user interaction reports whenever a user engages with the digital content. The system may aggregate the interaction reports to generate an affinity profile for a user or audience of users. A marketer may then generate digital content for a target user or audience of users and the system may process the digital content to generate a set of tags for the digital content. Based on the set of tags, the system may then evaluate the digital content in view of the affinity profile for the target user/audience to determine similarities or differences between the digital content and the affinity profile.
    Type: Grant
    Filed: September 16, 2021
    Date of Patent: June 11, 2024
    Assignee: Adobe Inc.
    Inventors: Yaman Kumar, Vinh Ngoc Khuc, Vijay Srivastava, Umang Moorarka, Sukriti Verma, Simra Shahid, Shirsh Bansal, Shankar Venkitachalam, Sean Steimer, Sandipan Karmakar, Nimish Srivastav, Nikaash Puri, Mihir Naware, Kunal Kumar Jain, Kumar Mrityunjay Singh, Hyman Chung, Horea Bacila, Florin Silviu Iordache, Deepak Pai, Balaji Krishnamurthy
  • Patent number: 11960520
    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.
    Type: Grant
    Filed: June 29, 2022
    Date of Patent: April 16, 2024
    Assignee: Adobe Inc.
    Inventors: Tanay Anand, Sumit Bhatia, Simra Shahid, Nikitha Srikanth, Nikaash Puri
  • Publication number: 20240004912
    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.
    Type: Application
    Filed: June 29, 2022
    Publication date: January 4, 2024
    Inventors: Tanay Anand, Sumit Bhatia, Simra Shahid, Nikitha Srikanth, Nikaash Puri
  • Publication number: 20230169271
    Abstract: Systems and methods for topic modeling are described. The systems and methods include encoding words of a document using an embedding matrix to obtain word embeddings for the document. The words of the document comprise a subset of words in a vocabulary, and the embedding matrix is trained as part of a topic attention network based on a plurality of topics. The systems and methods further include encoding a topic-word distribution matrix using the embedding matrix to obtain a topic embedding matrix. The topic-word distribution matrix represents relationships between the plurality of topics and the words of the vocabulary. The systems and methods further include computing a topic context matrix based on the topic embedding matrix and the word embeddings and identifying a topic for the document based on the topic context matrix.
    Type: Application
    Filed: December 17, 2021
    Publication date: June 1, 2023
    Inventors: Shashank Shailabh, Madhur Panwar, Milan Aggarwal, Pinkesh Badjatiya, Simra Shahid, Nikaash Puri, S Sejal Naidu, Sharat Chandra Racha, Balaji Krishnamurthy, Ganesh Karbhari Palwe
  • Publication number: 20230143777
    Abstract: A method of finding online relevant conversing posts, comprises receiving, by a web server serving an online forum, a query post from an inquirer using the online forum, computing a contextual similarity score between each conversing post of a set of conversing posts with a query post, wherein the contextual similarity score is computed between the body of each of conversing posts and of the query post, wherein N1 conversing posts with a highest contextual similarity score are selected; computing a fine grained similarity score between the subject of the query post and of each of the N1 conversing posts, wherein N2 conversing posts with a highest fine grained similarity score are selected; and boosting the fine grained similarity score of the N2 conversing posts based on relevance metrics, wherein N3 highest ranked conversing posts are selected as a list of conversing posts most relevant to the query post.
    Type: Application
    Filed: November 10, 2021
    Publication date: May 11, 2023
    Inventors: Pinkesh BADJATIYA, Tanay ANAND, Simra SHAHID, Nikaash PURI, Milan AGGARWAL, S Sejal NAIDU, Sharat Chandra RACHA
  • Publication number: 20230085466
    Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for determining user affinities by tracking historical user interactions with tagged digital content and using the user affinities in content generation applications. Accordingly, the system may track user interactions with published digital content in order to generate user interaction reports whenever a user engages with the digital content. The system may aggregate the interaction reports to generate an affinity profile for a user or audience of users. A marketer may then generate digital content for a target user or audience of users and the system may process the digital content to generate a set of tags for the digital content. Based on the set of tags, the system may then evaluate the digital content in view of the affinity profile for the target user/audience to determine similarities or differences between the digital content and the affinity profile.
    Type: Application
    Filed: September 16, 2021
    Publication date: March 16, 2023
    Inventors: Yaman Kumar, Vinh Ngoc Khuc, Vijay Srivastava, Umang Moorarka, Sukriti Verma, Simra Shahid, Shirsh Bansal, Shankar Venkitachalam, Sean Steimer, Sandipan Karmakar, Nimish Srivastav, Nikaash Puri, Mihir Naware, Kunal Kumar Jain, Kumar Mrityunjay Singh, Hyman Chung, Horea Bacila, Florin Silviu Iordache, Deepak Pai, Balaji Krishnamurthy