- 专利标题: Training a question-answer dialog sytem to avoid adversarial attacks
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申请号: US17076031申请日: 2020-10-21
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公开(公告)号: US11520829B2公开(公告)日: 2022-12-06
- 发明人: Sara Rosenthal , Avirup Sil , Mihaela Ancuta Bornea , Radu Florian
- 申请人: International Business Machines Corporation
- 申请人地址: US NY Armonk
- 专利权人: International Business Machines Corporation
- 当前专利权人: International Business Machines Corporation
- 当前专利权人地址: US NY Armonk
- 代理商 Caleb D. Wilkes
- 主分类号: G06F16/9032
- IPC分类号: G06F16/9032 ; G06F21/54 ; G06N20/00
摘要:
A method, computer program product, and/or computer system protects a question-answer dialog system from being attacked by adversarial statements that incorrectly answer a question. A computing device accesses a plurality of adversarial statements that are capable of making an adversarial attack on a question-answer dialog system, which is trained to provide a correct answer to a specific type of question. The computing device utilizes the plurality of adversarial statements to train a machine learning model for the question-answer dialog system. The computing device then reinforces the trained machine learning model by bootstrapping adversarial policies that identify multiple types of adversarial statements onto the trained machine learning model. The computing device then utilizes the trained and bootstrapped machine learning model to avoid adversarial attacks when responding to questions submitted to the question-answer dialog system.
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