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How Context Affects Language Models' Factual Predictions
[article]
2020
arXiv
pre-print
When pre-trained on large unsupervised textual corpora, language models are able to store and retrieve factual knowledge to some extent, making it possible to use them directly for zero-shot cloze-style question answering. However, storing factual knowledge in a fixed number of weights of a language model clearly has limitations. Previous approaches have successfully provided access to information outside the model weights using supervised architectures that combine an information retrieval
arXiv:2005.04611v1
fatcat:uylkyzvscve5dgcofihq7g3mfu