Oracle International Corporation

Zikai Li

Mark Edward Johnson

Thanh Long Duong

Vishal Vishnoi

Srinivasa Phani Kumar Gadde

Elias Luqman Jalaluddin

Cong Duy Vu Hoang

Poorya Zaremoodi

Tuyen Quang Pham

Aashna Devang Kanuga

Yuanxu Wu

Techniques are disclosed for systems including techniques for multi-feature balancing for natural langue processors. In an embodiment, a method includes receiving a natural language query to be processed by a machine learning model, the machine learning model utilizing a dataset of natural language phrases for processing natural language queries, determining, based on the machine learning model and the natural language query, a feature dropout value, generating, and based on the natural language query, one or more contextual features and one or more expressional features that may be input to the machine learning model, modifying at least one or the one or more contextual features and the one or more expressional features based on the feature dropout value to generate a set of input features for the machine learning model, and processing the set of input features to cause generating an output dataset for corresponding to the natural language query.

Multi-feature balancing for natural language processors

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Redwood City, CA, United States of America

Zikai Li