Everything on Data Quality

Extracting data from literature via LLMs introduces risks of false positives and discrepancies between graphical data and author interpretations.

Impact: Implementing robust verification protocols for literature-extracted data prevents model contamination and ensures training datasets reflect accurate experimental outcomes.

— from AI in Materials Science: Discovery, Data Gaps, and Active Learning · Latent Space: The AI Engineer Podcast· Mar 24, 2026