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Melika Behjati

2 accepted papers

2023

Learning to Abstract with Nonparametric Variational Information Bottleneck

EMNLP 2023short findings

Learned representations at the level of characters, sub-words, words, and sentences, have each contributed to advances in understanding different NLP tasks and linguistic phenomena. However, learning textual embeddings is costly as they are tokenization specific and require different models to be tr…

Cited by 0SourceScholar
2019

Universal Adversarial Attacks on Text Classifiers

ICASSP 2019accepted

Despite the vast success neural networks have achieved in different application domains, they have been proven to be vulnerable to adversarial perturbations (small changes in the input), which lead them to produce the wrong output. In this paper, we propose a novel method, based on gradient projecti…

Cited by 0SourceScholar