Invention Application
- Patent Title: Machine-Learned Models for User Interface Prediction, Generation, and Interaction Understanding
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Application No.: US17335596Application Date: 2021-06-01
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Publication No.: US20220382565A1Publication Date: 2022-12-01
- Inventor: Srinivas Kumar Sunkara , Xiaoxue Zang , Ying Xu , Lijuan Liu , Nevan Holt Wichers , Gabriel Overholt Schubiner , Jindong Chen , Abhinav Kumar Rastogi , Blaise Aguera-Arcas , Zecheng He
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Main IPC: G06F9/451
- IPC: G06F9/451 ; G06N20/00 ; G06N3/04 ; G06K9/62

Abstract:
Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface prediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).
Public/Granted literature
- US11789753B2 Machine-learned models for user interface prediction, generation, and interaction understanding Public/Granted day:2023-10-17
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