9 citations · 14 across the 16 of their papers we have counts for
3 papers · 1 filter
Learning-Time Encoding Shapes Unlearning in LLMs
Ruihan Wu, Konstantin Garov, Kamalika Chaudhuri
As large language models (LLMs) are increasingly deployed in the real world, the ability to ``unlearn'', or remove specific pieces of knowledge post hoc, has become essential for a…
Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu +9
Machine unlearning techniques aim to mitigate unintended memorization in large language models (LLMs). However, existing approaches predominantly focus on the explicit removal of i…
Evaluating Deep Unlearning in Large Language Models
Ruihan Wu, Chhavi Yadav, Russ Salakhutdinov +1
Machine unlearning has emerged as an important component in developing safe and trustworthy models. Prior work on fact unlearning in LLMs has mostly focused on removing a specified…