Invention Grant
- Patent Title: Generating summary content tuned to a target characteristic using a word generation model
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Application No.: US17348257Application Date: 2021-06-15
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Publication No.: US11657225B2Publication Date: 2023-05-23
- Inventor: Balaji Vasan Srinivasan , Kushal Chawla , Mithlesh Kumar , Hrituraj Singh , Arijit Pramanik
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06F40/284
- IPC: G06F40/284 ; G06N20/00

Abstract:
Systems and methods for generating a tuned summary using a word generation model. An example method includes receiving, at a decoder of the word generation model, a training data learned subspace representation of training data. The method also includes identifying tunable linguistic characteristics of the word generation model and training the decoder to output a training tuned summary of the training data learned subspace representation based on at least one of the tunable linguistic characteristics. The method further includes receiving an input text and a target characteristic token, and generating, by the trained decoder of the word generation model, each word of a tuned summary of the input text from a learned subspace representation and from feedback about preceding words of the tuned summary, wherein the tuned summary is tuned to target characteristics represented by the target characteristic token.
Public/Granted literature
- US20210312129A1 GENERATING SUMMARY CONTENT TUNED TO A TARGET CHARACTERISTIC USING A WORD GENERATION MODEL Public/Granted day:2021-10-07
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