Invention Grant
- Patent Title: Contextual text generation for question answering and text summarization with supervised representation disentanglement and mutual information minimization
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Application No.: US17114946Application Date: 2020-12-08
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Publication No.: US11887008B2Publication Date: 2024-01-30
- Inventor: Renqiang Min , Christopher Malon , Hans Peter Graf
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Corporation
- Current Assignee: NEC Corporation
- Current Assignee Address: JP Tokyo
- Agent Joseph Kolodka
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/088 ; G06F40/20 ; G10L15/06 ; G10L15/16 ; G10L15/22 ; G06N3/086 ; G06N3/02 ; G06N3/082

Abstract:
Methods and systems for disentangled data generation include accessing a dataset including pairs, each formed from a given input text structure and a given style label for the input text structures. An encoder is trained to disentangle a sequential text input into disentangled representations, including a content embedding and a style embedding, based on a subset of the dataset, using an objective function that includes a regularization term that minimizes mutual information between the content embedding and the style embedding. A generator is trained to generate a text output that includes content from the style embedding, expressed in a style other than that represented by the style embedding of the text input.
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Information query