Papers by Aarohi Srivastava

1 papers
BERTwich: Extending BERT’s Capabilities to Model Dialectal and Noisy Text (2023.findings-emnlp)

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Challenge: Pre-trained language models like BERT deteriorate in the face of dialect variation or noise.
Approach: They propose to sandwich BERT's encoder stack between additional encoder layers trained to perform masked language modeling on noisy text.
Outcome: The proposed approach promotes zero-shot transfer to dialectal text and reduces embedding space between words and noisy counterparts.

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