Invention Grant
- Patent Title: Continuous learning for natural-language understanding models for assistant systems
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Application No.: US17351501Application Date: 2021-06-18
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Publication No.: US11861315B2Publication Date: 2024-01-02
- Inventor: Pooja Sethi , Denis Savenkov , Yue Liu , Alexander Kolmykov-Zotov , Ahmed Aly
- Applicant: Meta Platforms, Inc.
- Applicant Address: US CA Menlo Park
- Assignee: Meta Platforms, Inc.
- Current Assignee: Meta Platforms, Inc.
- Current Assignee Address: US CA Menlo Park
- Agency: Baker Botts L.L.P.
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F40/30 ; G06F1/3206 ; G06F3/01 ; G06F3/04815 ; G06N5/02 ; G06N5/046 ; G06T19/00 ; G06T19/20

Abstract:
In one embodiment, a method includes receiving a user request to automatically debug a natural-language understanding (NLU) model, accessing a plurality of predicted semantic representations generated by the NLU model, wherein the plurality of predicted semantic representations are associated with a plurality of dialog sessions, respectively, wherein each dialog session is between a user and an assistant xbot associated with the NLU model, generating a plurality of expected semantic representations associated with the plurality of dialog sessions based on an auto-correction model, wherein the auto-correction model is learned from dialog training samples generated based on active learning, identifying incorrect semantic representations of the predicted semantic representations based on a comparison between the predicted semantic representations and the expected semantic representations, and automatically correcting the incorrect semantic representations by replacing them with respective expected semantic representations generated by the auto-correction model.
Public/Granted literature
- US20220374605A1 Continuous Learning for Natural-Language Understanding Models for Assistant Systems Public/Granted day:2022-11-24
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