Papers by Zixiong Wang

1 papers
Decoupling Memories, Muting Neurons: Towards Practical Machine Unlearning for Large Language Models (2025.findings-acl)

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Challenge: Existing methods for MU degrade model utility, especially when accessing the original training data.
Approach: They propose a method that eliminates the influence of unlearned data by modulating the outputs of merely 1% of the neurons in the feed-forward network modules within the Transformer blocks.
Outcome: The proposed method eliminates the influence of unlearned data from Large Language Models by modulating the outputs of 1% of the neurons in the feed-forward network modules within the Transformer blocks, minimizing disruption to the model’s performance.

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