Papers with MEMIT-Merge

    1 papers
    MEMIT-Merge: Addressing MEMIT’s Key-Value Conflicts in Same-Subject Batch Editing for LLMs (2025.findings-acl)

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    Challenge: Existing knowledge editing techniques that modify models’ internal knowledge without full model retraining have gained significant attention.
    Approach: They propose an enhanced approach that merges value computation processes for facts sharing the same subject to improve editing efficiency.
    Outcome: The proposed method maintains a 98% editing success rate on same-subject and distinct-sub subject datasets while the original success rate drops to 46%.

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