3 papers
astro-ph.IM2025
Multi-Modal Masked Autoencoders for Learning Image-Spectrum Associations for Galaxy Evolution and Cosmology
Morgan Himes, Samiksha Krishnamurthy, Andrew Lizarraga +5
Upcoming surveys will produce billions of galaxy images but comparatively few spectra, motivating models that learn cross-modal representations. We build a dataset of 134,533 galax…
astro-ph.GA2025
Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models
Andrew Lizarraga, Eric Hanchen Jiang, Jacob Nowack +4
Redshift measures the distance to galaxies and underlies our understanding of the origin of the Universe and galaxy evolution. Spectroscopic redshift is the gold-standard method fo…
cs.CL2025
Better Prompt Compression Without Multi-Layer Perceptrons
Edouardo Honig, Andrew Lizarraga, Zijun Frank Zhang +1
Prompt compression is a promising approach to speeding up language model inference without altering the generative model. Prior works compress prompts into smaller sequences of lea…