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Finally, a dataset exists to train and benchmark algorithms for automatically detecting airway bifurcations in 3D CT scans, a crucial step towards understanding respiratory diseases.
Unlock precise, training-free color control in text-to-image models by directly manipulating the latent space's emergent Hue, Saturation, and Lightness structure.
Achieve meaningful vision-language model alignment with significantly less supervision by leveraging unpaired data via optimal transport.
Unlocking VLM interpretability, sparse autoencoders let you directly steer multimodal LLMs like LLaVA by intervening on CLIP's vision encoder.
