Papers with model editing task

1 papers
Correcting Language Model Outputs by Editing Salient Layers (2024.findings-eacl)

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Challenge: Existing models that use manual layer selection require prior domain knowledge and expensive empirical layer selection methods.
Approach: They propose a model editing approach that selectively edits a small subset of model parameters to update the factual knowledge.
Outcome: The proposed solution matches the accuracy of previous approaches with only 1/3 of their edits, enabling efficient updates to the parametric knowledge in large language models.

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