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Found 3 papers, 2 papers with code
The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes
Inspired by this, we introduce a new method for estimating the influence of training data, which requires calculating gradients for specific test samples, paired with a forward pass for each training point.
Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study
Furthermore, our enhanced attacks outperform the baseline across multiple models and datasets, with the weakly supervised attack demonstrating an average-case performance improvement of $17\%$ and being at least $7$X more effective at low false-positive rates.
LAVA: Data Valuation without Pre-Specified Learning Algorithms
(1) We develop a proxy for the validation performance associated with a training set based on a non-conventional class-wise Wasserstein distance between training and validation sets.
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