Teaching Gemini to spot exploding stars with just a few examples
Google Research
Researchers trained Google's Gemini model to classify astronomical events like supernovae by providing just 15 annotated examples per survey, rather than requiring millions of labeled images like traditional specialized models. The model achieved 93% accuracy across three major surveys (Pan-STARRS, MeerLICHT, and ATLAS) while generating human-readable explanations of its classifications and can assess its own uncertainty to flag uncertain cases. This approach enables transparent decision-making for astronomers processing millions of nightly alerts and can be rapidly adapted to new telescopes and scientific domains.
Why it matters
General Science
