3 citations · 3 across the 10 of their papers we have counts for
3 papers · 1 filter
SHRED: Retain-Set-Free Unlearning via Self-Distillation with Logit Demotion
Zizhao Hu, Ameya Godbole, Johnny Tian-Zheng Wei +3
Machine unlearning for large language models (LLMs) aims to selectively remove memorized content such as private data, copyrighted text, or hazardous knowledge, without costly full…
Correcting test set contamination by spiking the training data
Johnny Tian-Zheng Wei, Jerry Li, Ameya Godbole +1
The literature on test set contamination largely focuses on detection, but the correction of contaminated test scores is underexplored. Our core proposal is to spike the training d…
Psychological Steering of Large Language Models
Leonardo Blas, Robin Jia, Emilio Ferrara
Large language models (LLMs) emulate a consistent human-like behavior that can be shaped through activation-level interventions. This paradigm is converging on additive residual-st…