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US Patent 11620515 Multi-task knowledge distillation for language model

Patent 11620515 was granted and assigned to Salesforce on April, 2023 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Salesforce
Salesforce
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Current Assignee
Salesforce
Salesforce
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
116205150
Patent Inventor Names
Caiming Xiong0
Linqing Liu0
Date of Patent
April 4, 2023
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Patent Application Number
167162490
Date Filed
December 16, 2019
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Patent Citations
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US Patent 10282663 Three-dimensional (3D) convolution with 3D batch normalization
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US Patent 10346721 Training a neural network using augmented training datasets
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US Patent 10474709 Deep reinforced model for abstractive summarization
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Patent Citations Received
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US Patent 11765193 Contextual embeddings for improving static analyzer output
Patent Primary Examiner
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Daniel C Washburn
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CPC Code
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G06F 40/30
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G06F 40/40
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G06F 40/216
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G06F 40/284
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G06N 3/0472
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G06N 3/0445
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G06N 3/0454
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G06N 3/08
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Systems and methods are provided that employ knowledge distillation under a multi-task learning setting. In some embodiments, the systems and methods are implemented with a larger teacher model and a smaller student model, each of which comprise one or more shared layers and a plurality of task layers for performing multiple tasks. During training of the teacher model, its shared layers are initialized, and then the teacher model is multi-task refined. The teacher model predicts teacher logits. During training of the student model, its shared layers are initialized. Knowledge distillation is employed to transfer knowledge from the teacher model to the student model by the student model updating its shared layers and task layers, for example, according to the teacher logits of the teacher model. Other features are also provided.

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