Papers by Jan Mackensen
BERT-Defense: A Probabilistic Model Based on BERT to Combat Cognitively Inspired Orthographic Adversarial Attacks (2021.findings-acl)
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| Challenge: | adversarial attacks expose important blind spots of deep learning systems, authors show . word and sentence-level attacks tend to be more difficult to defend via spelling correction modules . character-level attack scenarios often involve finding semantic paraphrases of input . |
| Approach: | They propose a model that probabilistically combines context-independent word level information with context-dependent information from BERT's masked language modeling to combat low-level orthographic attacks. |
| Outcome: | The proposed model outperforms a spellchecker and Pruthi's model on a character-level benchmark. |