MACHINE LEARNING MODEL ALIGNMENT
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United States of America
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Issued Date -
Jan 16, 2025
app pub date -
Sep 27, 2024
filing date -
Sep 27, 2024
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Abstract
A method is proposed for machine learning (ML) model alignment. In the method, a first number of samples is generated by a target ML model based on samples selected from a set of samples. A sample comprises a question-answer pair. The set of samples is updated by adding at least a portion of the first number of samples to the set of samples. The target ML model is trained with at least a portion of the updated set of samples. In this way, the ML model self-generalization ability is unlocked to perform alignment with near-zero human supervision.
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