Papers with external knowledge integration

1 papers
Interpretability-based Tailored Knowledge Editing in Transformers (2024.emnlp-main)

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Challenge: Existing methods for modifying in-context learning fail to analyze the instability of in-constitu learning outcomes.
Approach: They propose a model-based knowledge editing method that considers the unique information flow of each sample and aims to correct errors without costly retraining.
Outcome: The proposed method exploits the critical role of feed-forward MLPs in decoder-only models and reveals diverse attribute recall across transformer layers, guiding edits to specific features at different depths and mitigating over-editing issues.

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