flâneur

Autodata: An agentic data scientist to create high quality synthetic data | alphaXiv

alphaxiv.org · 1,503 words · saved by 1 readers

Autodata introduces an agentic framework for autonomously generating and curating high-quality synthetic data to train large language models (LLMs). Through iterative feedback and meta-optimization...

The Agentic Data Scientist Paradigm The trajectory of modern artificial intelligence is increasingly defined by the availability and quality of training data. While initial progress relied heavily on human-curated datasets, the frontier of AI research has shifted toward synthetic data generation—using existing models to create the next generation of training material. However, traditional synthetic data pipelines often function as static, one-way processes: a prompt is provided, data is generated, and perhaps a filter is applied. These methods frequently struggle to produce data that is…

saved by

related reading