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Found 2 papers, 2 papers with code
Neural Networks Learn Statistics of Increasing Complexity
The distributional simplicity bias (DSB) posits that neural networks learn low-order moments of the data distribution first, before moving on to higher-order correlations.
Text Counterfactuals via Latent Optimization and Shapley-Guided Search
We study the problem of generating counterfactual text for a classifier as a means for understanding and debugging classification.
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