Automatically Synthesizing Data Quality Assertions for Large Language Model Pipelines

Developers can automatically generate a minimal set of data quality assertions that identify errors in the outputs of large language model (LLM) pipelines, by analyzing prompt version histories and filtering candidate assertions based on coverage and accuracy requirements.