Invention Grant
- Patent Title: Systems and methods for factual extraction from language model
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Application No.: US17588043Application Date: 2022-01-28
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Publication No.: US12112131B2Publication Date: 2024-10-08
- Inventor: Benjamin Newman , Nazneen Rajani , Prafulla Kumar Choubey
- Applicant: Salesforce, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Salesforce, Inc.
- Current Assignee: Salesforce, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Haynes and Boone, LLP
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06F3/08 ; G06F40/126 ; G06F40/279 ; G06N3/044

Abstract:
Embodiments described herein provide a system and method for extracting factual information. The system transforms a query into a natural language prompt in a format of a query subject and a queried relation. The system encodes, via an embedding layer of a pre-trained language model, the natural language prompt into a first embedding. The system encodes, via the adapter model, the first embedding into a second embedding based on a probability that the second embedding returns the factual information when the second embedding is fed the first attention layer of the pre-trained language model. The system decodes, by the first attention layer of the pre-trained language mode, the second embedding into a response to the query. The system extracts the factual information from the decoded response to the query.
Public/Granted literature
- US20230083512A1 SYSTEMS AND METHODS FOR FACTUAL EXTRACTION FROM LANGUAGE MODEL Public/Granted day:2023-03-16
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