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cs.LG2026
EmbeddGAN: A Novel GAN Framework Using an Embedding Network and Gini Distance Correlation
MaTais Caldwell, Yixin Chen, Xin Dang +1
Generative Adversarial Networks (GANs) have demonstrated strong performance in generating high-quality synthetic data. However, they are limited by no formal guarantees regarding c…
cs.CV2026
Restrict, Don't Retrain: Inference-Time VLM Guidance for Zero-Shot Aerial Segmentation
Teresa DiMeola, Charles Walter, Hong Xiao
Global welfare often depends on the correct interpretation of aerial and satellite imagery. Acting on such imagery (mapping flooded ground, crop extent, or damaged infrastructure)…