A framework that applies provenance-based guidance to input gradients during synthetic data training to promote learning from target regions only.
Mitigating Simplicity Bias in Neural Net- works: A Feature Sieve Modification, Regularization, and Self-Supervised Augmentation Approach
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Learning from Synthetic Data via Provenance-Based Input Gradient Guidance
A framework that applies provenance-based guidance to input gradients during synthetic data training to promote learning from target regions only.