Vision-language models underperform specialized astronomical methods on real observational data, with accuracy improving when physical explanations are provided in prompts and when raw numerical measurements replace rendered plots.
Avocado: Photometric classification of astronomical transients with gaussian process augmentation.AJ, 158(6):257, December 2019
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SCAT DR1 delivers 1810 spectra of 1330 transients with classifications, fitted light curves, new redshifts for many host galaxies, and host properties as a testbed for photometric classification pipelines.
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A systematic evaluation of vision-language models for observational astronomical reasoning tasks
Vision-language models underperform specialized astronomical methods on real observational data, with accuracy improving when physical explanations are provided in prompts and when raw numerical measurements replace rendered plots.
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SCAT Data Release 1: 1810 optical spectra of 1330 transients
SCAT DR1 delivers 1810 spectra of 1330 transients with classifications, fitted light curves, new redshifts for many host galaxies, and host properties as a testbed for photometric classification pipelines.