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：US11983946B2

公开(公告)日：2024-05-14

申请号：US17517434

申请日：2021-11-02

Applicant: Adobe Inc.

Inventor： Shripad Deshmukh ,  Milan Aggarwal ,  Mausoom Sarkar ,  Hiresh Gupta

IPC: G06V30/414 ,  G06F18/21 ,  G06N3/08 ,  G06V10/94 ,  G06V30/18 ,  G06V30/262

CPC classification number: G06V30/414 ,  G06F18/21 ,  G06N3/08 ,  G06V10/95 ,  G06V30/18 ,  G06V30/274

Abstract: In implementations of refining element associations for form structure extraction, a computing device implements a structure system to receive estimate data describing estimated associations of elements included in a form and a digital image depicting the form. An image patch is extracted from the digital image, and the image patch depicts a pair of elements of the elements included in the form. The structure system encodes an indication of whether the pair of elements have an association of the estimated associations. An indication is generated that the pair of elements have a particular association based at least partially on the encoded indication, bounding boxes of the pair of elements, and text depicted in the image patch.

公开(公告)号：US11948358B2

公开(公告)日：2024-04-02

申请号：US17455126

申请日：2021-11-16

Applicant: ADOBE INC.

Inventor： Sumegh Roychowdhury ,  Sumedh A. Sontakke ,  Mausoom Sarkar ,  Nikaash Puri ,  Pinkesh Badjatiya ,  Milan Aggarwal

IPC: G06V20/40 ,  G06N3/088

CPC classification number: G06V20/41 ,  G06N3/088 ,  G06V20/47 ,  G06V20/44

Abstract: Systems and methods for video processing are described. Embodiments of the present disclosure generate a plurality of image feature vectors corresponding to a plurality of frames of a video; generate a plurality of low-level event representation vectors based on the plurality of image feature vectors, wherein a number of the low-level event representation vectors is less than a number of the image feature vectors; generate a plurality of high-level event representation vectors based on the plurality of low-level event representation vectors, wherein a number of the high-level event representation vectors is less than the number of the low-level event representation vectors; and identify a plurality of high-level events occurring in the video based on the plurality of high-level event representation vectors.

公开(公告)号：US20220245141A1

公开(公告)日：2022-08-04

申请号：US17656772

申请日：2022-03-28

Applicant: Adobe Inc.

Inventor： Milan Aggarwal ,  Balaji Krishnamurthy

IPC: G06F16/242 ,  G06N20/00 ,  G06F16/248

Abstract: An interactive search session is implemented using an artificial intelligence model. For example, when the artificial intelligence model receives a search query from a user, the model selects an action from a plurality of actions based on the search query. The selected action queries the user for more contextual cues about the search query (e.g., may enquire about use of the search results, may request to refine the search query, or otherwise engage the user in conversation to better understand the intent of the search). The interactive search session may be in the form, for example, of a chat session between the user and the system, and the chat session may be displayed along with the search results (e.g., in a separate section of display). The interactive search session may enable the system to better understand the user's search needs, and accordingly may help provide more focused search results.

公开(公告)号：US11294891B2

公开(公告)日：2022-04-05

申请号：US16394853

申请日：2019-04-25

Applicant: Adobe Inc.

Inventor： Milan Aggarwal ,  Balaji Krishnamurthy

IPC: G06F16/332 ,  G06F16/242 ,  G06N20/00 ,  H04L51/02 ,  G06F40/205

Abstract: Techniques are disclosed for providing an interactive search session. The interactive search session is implemented using an artificial intelligence model. For example, when the artificial intelligence model receives a search query from a user, the model selects an action from a plurality of actions based on the search query. The selected action queries the user for more contextual cues about the search query (e.g., may enquire about use of the search results, may request to refine the search query, or otherwise engage the user in conversation to better understand the intent of the search). The interactive search session may be in the form, for example, of a chat session between the user and the system, and the chat session may be displayed along with the search results (e.g., in a separate section of display). The interactive search session may enable the system to better understand the user's search needs, and accordingly may help provide more focused search results.

公开(公告)号：US20200341976A1

公开(公告)日：2020-10-29

申请号：US16394853

申请日：2019-04-25

Applicant: Adobe Inc.

Inventor： Milan Aggarwal ,  Balaji Krishnamurthy

IPC: G06F16/242 ,  H04L12/58 ,  G06N20/00

Abstract: Techniques are disclosed for providing an interactive search session. The interactive search session is implemented using an artificial intelligence model. For example, when the artificial intelligence model receives a search query from a user, the model selects an action from a plurality of actions based on the search query. The selected action queries the user for more contextual cues about the search query (e.g., may enquire about use of the search results, may request to refine the search query, or otherwise engage the user in conversation to better understand the intent of the search). The interactive search session may be in the form, for example, of a chat session between the user and the system, and the chat session may be displayed along with the search results (e.g., in a separate section of display). The interactive search session may enable the system to better understand the user's search needs, and accordingly may help provide more focused search results.

公开(公告)号：US20200302016A1

公开(公告)日：2020-09-24

申请号：US16359402

申请日：2019-03-20

Applicant: Adobe Inc.

Inventor： Milan Aggarwal ,  Balaji Krishnamurthy

IPC: G06F17/27 ,  G06F16/93 ,  G06N3/08 ,  G06N3/04 ,  G10L15/02

Abstract: Classifying structural features of a digital document by feature type using machine learning is leveraged in a digital medium environment. A document analysis system is leveraged to extract structural features from digital documents, and to classifying the structural features by respective feature types. To do this, the document analysis system employs a character analysis model and a classification model. The character analysis model takes text content from a digital document and generates text vectors that represent the text content. A vector sequence is generated based on the text vectors and position information for structural features of the digital document, and the classification model processes the vector sequence to classify the structural features into different feature types. The document analysis system can generate a modifiable version of the digital document that enables its structural features to be modified based on their respective feature types.

公开(公告)号：US10713317B2

公开(公告)日：2020-07-14

申请号：US15419497

申请日：2017-01-30

Applicant: ADOBE INC.

Inventor： Balaji Krishnamurthy ,  Shagun Sodhani ,  Aarushi Arora ,  Milan Aggarwal

IPC: G06F16/9535 ,  G06F16/9032 ,  G06N3/00 ,  G06N20/00 ,  G06F40/30 ,  G06F40/35 ,  G06N3/08 ,  G06N7/00

Abstract: A conversational agent facilitates conversational searches for users. The conversational agent is a reinforcement learning (RL) agent trained using a user model generated from existing session logs from a search engine. The user model is generated from the session logs by mapping entries from the session logs to user actions understandable by the RL agent and computing conditional probabilities of user actions occurring given previous user actions in the session logs. The RL agent is trained by conducting conversations with the user model in which the RL agent selects agent actions in response to user actions sampled using the conditional probabilities from the user model.

公开(公告)号：US12265792B2

公开(公告)日：2025-04-01

申请号：US17526824

申请日：2021-11-15

Applicant: ADOBE INC.

Inventor： Rachit Bansal ,  Milan Aggarwal ,  Sumit Bhatia ,  Jivat Neet Kaur ,  Balaji Krishnamurthy

IPC: G06F40/295 ,  G06F16/332 ,  G06F16/3329 ,  G06N20/00

Abstract: Methods and systems are provided for facilitating generation and utilization of a commonsense contextualizing machine learning (ML) model, in accordance with embodiments described herein. In embodiments, a commonsense contextual ML model is trained by fine-tuning a pre-trained language model using a set of training path-sentence pairs. Each training path-sentence pair includes a commonsense path, identified via a commonsense knowledge graph, and a natural language sentence identified as contextually related to the commonsense path. The trained commonsense contextualizing ML model can then be used to generate a commonsense inference path for a text input. Such a commonsense inference path can include a sequence of entities and relations that provide commonsense context to the text input. Thereafter, the commonsense inference path can be provided to a natural language processing system for use in performing a natural language processing task.

公开(公告)号：US12190061B2

公开(公告)日：2025-01-07

申请号：US17644856

申请日：2021-12-17

Applicant: ADOBE INC.

Inventor： Shashank Shailabh ,  Madhur Panwar ,  Milan Aggarwal ,  Pinkesh Badjatiya ,  Simra Shahid ,  Nikaash Puri ,  S Sejal Naidu ,  Sharat Chandra Racha ,  Balaji Krishnamurthy ,  Ganesh Karbhari Palwe

IPC: G06F40/289 ,  G06F40/30 ,  G06F40/40

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.