Oracle International Corporation

Jason Anthony Peck

Michael Louis Wick

Jean-Baptiste Frederic George Tristan

Swetasudha Panda

Ariel Gedaliah Kobren

Qinlan Shen

Techniques are disclosed for augmenting data sets used for training machine learning models and for generating predictions by trained machine learning models. These techniques may increase a number and diversity of examples within an initial training dataset of sentences by extracting a subset of words from the existing training dataset of sentences. The techniques may conserve scarce sample data in few-shot situations by training a data generation model using general data obtained from a general data source.

Guided augmentation of data sets for machine learning models

A method of evaluating a language model using negative data may include accessing a first language model that is trained using a first training corpus, and accessing a second language model. The second language model may be configured to generate outputs that are less grammatical than outputs generated by the first language model. The method may also include training the second language model using a second training corpus, and generating output text from the second language model. The method may further include testing the first language model using the output text from the second language model.

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Andover, MA, United States of America

Jason Anthony Peck