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CritiQ: Mining Data Quality Criteria from Human Preferences

Guo, Honglin et al.
arXiv (OAI Expanded) · Papers
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computation-and-language
Language model heavily depends on high-quality data for optimal performance. Existing approaches rely on manually designed heuristics, the perplexity of existing models, training classifiers, or careful prompt engineering, which require significant expert experience and human annotation effort while
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