Intuit, Inc.

Tak Yiu Daniel Li

Harpreet Singh Hira

Priyadarshini Rajendran

Sanmathi Sathyanarayana Naga

Nicholas Allen McHenry

Abhay Dhundiraju Sastry

Majo Paulose

Jasen Paul Stine

Darpan Sharma

Tharathorn Joy Rimchala

Peter Lee Frick

Karelia Del Carmen Pena Pena

Certain aspects of the present disclosure provide techniques for providing sentiment analysis of content. In order to determine the overall sentiment of content, a request is received by a sentiment analyzer, which then identifies a content identification number and retrieves comments associated with the content identification number. The sentiment analyzer pre-processes the comments, which includes removing all personal identifying information from the comments. The sentiment analyzer sends the pre-processed comments to a natural language processing service, and in turn, receives sentiment indications corresponding to the comments provided. Based on the sentiment scores, the sentiment analyzer generates a sentiment analysis and displays the sentiment analysis in the graphical user interface generated by the sentiment analyzer.

Generating sentiment analysis of content

Certain aspects of the disclosure provide systems and methods for training an information extraction transformer model architecture directed to pre-training a first multimodal transformer model on an unlabeled dataset, training a second multimodal transformer model on a first labeled dataset to perform a key information extraction task processing the unlabeled dataset with the second multimodal transformer model to generate pseudo-labels for the unlabeled dataset, training the first multimodal transformer model based on a second labeled dataset comprising one or more labels, the pseudo-labels generated, or combinations thereof to generate a third multimodal transformer model, generating updated pseudo-labels based on label completion predictions from the third multimodal transformer model, and training the third multimodal transformer model using a noise-aware loss function and the updated pseudo-labels to generate an updated third multimodal transformer model.

Systems and methods for training an information extraction transformer model architecture

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Frisco, TX, United States of America

Tak Yiu Daniel Li