Machine-learned models for user interface prediction, generation, and interaction understanding
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 usin...
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| creator | Wichers, Nevan Holt Zang, Xiaoxue He, Zecheng Sunkara, Srinivas Kumar Chen, Jindong Schubiner, Gabriel Overholt Aguera-Arcas, Blaise Rastogi, Abhinav Kumar Liu, Lijuan Xu, Ying |
| description | 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.). |
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| title | Machine-learned models for user interface prediction, generation, and interaction understanding |
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