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cs.LG2024
Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness
David Khachaturov, Robert Mullins
Quantifying robustness in a single measure for the purposes of model selection, development of adversarial training methods, and anticipating trends has so far been elusive. The si…
cs.CR2024★ 1 cited
Scaling Trends for Data Poisoning in LLMs
Dillon Bowen, Brendan Murphy, Will Cai +3
LLMs produce harmful and undesirable behavior when trained on datasets containing even a small fraction of poisoned data. We demonstrate that GPT models remain vulnerable to fine-t…
cs.LG2024
QBI: Quantile-Based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning
Micha V. Nowak, Tim P. Bott, David Khachaturov +3
Federated learning enables the training of machine learning models on distributed data without compromising user privacy, as data remains on personal devices and only model updates…