Papers by Michael Tänzer

1 papers
Memorisation versus Generalisation in Pre-trained Language Models (2022.acl-long)

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Challenge: State-of-the-art pre-trained language models have been shown to memorise facts and perform well with limited amounts of training data.
Approach: They propose to extend pre-trained language models to generalise and memorise facts in noisy and low-resource scenarios.
Outcome: The proposed extension improves performance in low-resource named entity recognition tasks.

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