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On the Robustness of Language Encoders against Grammatical Errors
[article]
2020
arXiv
pre-print
We conduct a thorough study to diagnose the behaviors of pre-trained language encoders (ELMo, BERT, and RoBERTa) when confronted with natural grammatical errors. Specifically, we collect real grammatical errors from non-native speakers and conduct adversarial attacks to simulate these errors on clean text data. We use this approach to facilitate debugging models on downstream applications. Results confirm that the performance of all tested models is affected but the degree of impact varies. To
arXiv:2005.05683v1
fatcat:6lo24qidevhtjduvef466wq4pe