Papers by Qiuyinzhe Zhang

1 papers
CritiQ: Mining Data Quality Criteria from Human Preferences (2025.acl-long)

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Challenge: Existing methods to train language models rely on manual design, perplexity, or careful prompt engineering.
Approach: They propose a method that automatically mines criteria from human preferences for data quality with only 30 human-annotated pairs and performs efficient data selection.
Outcome: The proposed method improves on human-annotated test sets and shows high accuracy on code, math, and logic domains.

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