Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond

Understand

Large-scale data collection is essential for developing personalized training data, mitigating the shortage of training data, and fine-tuning specialized models.

• However, creating high-quality datasets quickly and accurately remains a challenge due to annotation errors, the substantial time and costs associated with human labor.
• To address these issues, we propose Automatic Dataset Construction (ADC), an innovative methodology that automates dataset creation with negligible cost and high efficiency.
• Taking the image classification task as a starting point, ADC leverages LLMs for the detailed class design and code generation to collect relevant samples via search engines, significantly reducing the need for manual annotation and speeding up the data generation process.