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Peking U & Microsoft’s Knowledge Attribution Method Enables Editing Factual Knowledge in Pretrained Transformers Without Fine-Tuning

While today’s large language models have demonstrated an impressive ability to extract and recall massive amounts of factual knowledge from their training data, the question of how this factual knowledge is stored in such models remains under-explored.

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