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cs.LG2025
Daunce: Data Attribution through Uncertainty Estimation
Xingyuan Pan, Chenlu Ye, Joseph Melkonian +2
Training data attribution (TDA) methods aim to identify which training examples influence a model's predictions on specific test data most. By quantifying these influences, TDA sup…
cs.LG2025
GraSS: Scalable Data Attribution with Gradient Sparsification and Sparse Projection
Pingbang Hu, Joseph Melkonian, Weijing Tang +2
Gradient-based data attribution methods, such as influence functions, are critical for understanding the impact of individual training samples without requiring repeated model retr…