Preprint
Jul 2026
RADIO1D: Elastic Representations for Condensed Vision Modeling
RADIO1D is introduced, which compresses images into a compact, variable-length 1D token sequence using multi-teacher knowledge distillation and an autoencoder design, delivering competitive performance on diverse multimodal benchmarks with lower computational overhead and better accuracy.
Greg Heinrich, Michael Ranzinger, Collin McCarthy et al.
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