Papers with large-scale language model pretraining

1 papers
An Empirical Revisiting of Linguistic Knowledge Fusion in Language Understanding Tasks (2022.emnlp-main)

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Challenge: Recent work attempts to explicitly incorporate human-defined linguistic priors into fine-tuning tasks.
Approach: They replace parsed graphs or trees with trivial ones to investigate linguistic priors . they propose to use trivial graphs as baselines to design advanced knowledge fusion methods .
Outcome: The use of trivial graphs improves performance in fully-supervised and few-shot settings.

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