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Found 3 papers, 1 papers with code
Evaluating the Ripple Effects of Knowledge Editing in Language Models
This has led to the development of various editing methods that allow updating facts encoded by the model.
LM vs LM: Detecting Factual Errors via Cross Examination
A prominent weakness of modern language models (LMs) is their tendency to generate factually incorrect text, which hinders their usability.
Crawling the Internal Knowledge-Base of Language Models
Here, we propose to address this goal by extracting a knowledge-graph of facts from a given language model.
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