Papers with enrichment process

1 papers
Dissecting Recall of Factual Associations in Auto-Regressive Language Models (2023.emnlp-main)

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Challenge: Existing studies have focused on identifying where factual knowledge is encoded in the network, but little is known about how it is extracted from the model parameters during inference.
Approach: They examine how factual associations are stored and retrieved internally in LMs . they use attention edges to identify critical points where information propagates to the prediction .
Outcome: The proposed model aggregates information about subject and relation to predict the correct attribute . the model “queries” the enriched subject to extract the attribute based on the proposed model .

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