Multiple Choice

A team is preparing a large dataset of user comments to train a powerful classification model. To ensure the data is high-quality, they first use a group of several smaller, independently trained models to evaluate each comment. They decide to discard any comment where the small models frequently disagree on the correct classification or where their combined prediction has very low confidence. What is the most likely rationale behind this data filtering strategy?

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Updated 2025-10-02

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Ch.4 Alignment - Foundations of Large Language Models

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