This paper establishes best practices for creating openly licensed training datasets for LLMs while addressing legal, ethical, and technical challenges in data collection and governance .
https://arxiv.org/abs/2501.08365
💡 Methods in this Paper:
→ Proposes seven core principles for dataset creation including fostering competition, enabling transparency, minimizing harms, supporting diversity, and ensuring data preservation
→ Introduces standardized metadata frameworks to track content licenses and permissions across jurisdictions
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🎯 Key Insights:
→ Public domain and openly licensed content can create competitive LLM training datasets
→ Machine-readable preference signals are crucial for sustainable data governance
→ Community-driven approaches similar to open source software can ensure dataset quality
→ Balancing openness with ethical considerations requires clear governance frameworks
→ Identified 480,000+ public domain books published between 1929-1989
→ Created frameworks adopted by 40,000+ software repositories
→ Established standards for 120+ languages in Mozilla Common Voice dataset
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