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A new MIT CSAIL study published in Nature Communications finds that individual training examples often have no measurable influence on any specific output of large generative image models, a phenomeno…

Researchers introduce C-VCE, a diffusion framework that builds a classifier directly into the generative model via a concept bottleneck layer to produce visual counterfactual explanations without rely…

Researchers introduced a novel regularizer based on conditional mutual information to enforce separation in deep learning models, balancing fairness and utility without sacrificing performance. The st…