Tag: adversarial machine learning
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Mapping Generalization Limits in Neural Program Synthesis
Explore how neural program synthesis models generalize beyond training data using controlled environments and semantic-syntactic metrics.
Debiasing Reward Models with Causal Inference Intervention
Reduce biases in reward models using causally motivated inference-time interventions to improve alignment with human preferences without losing performance...
Enhancing Graph Few-Shot Learning with Hyperbolic Space
Discover how hyperbolic space and denoising diffusion improve graph few-shot learning for better accuracy with limited data.
ABC Model: Advanced Any-Subset Autoregression in Continuous Time
Discover the ABC model for flexible, accurate stochastic process generation using non-Markovian diffusion bridges in continuous time and space.
TypeBandit: Efficient Attribute Completion in Heterogeneous GNNs
Discover TypeBandit, a novel method for effective attribute completion in heterogeneous graph neural networks with type-level context allocation.