Papers by Elena Burceanu

2 papers
Rethinking the Authorship Verification Experimental Setups (2022.emnlp-main)

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Challenge: Identifying the author of a text is one of the most versatile NLP tasks, with applications ranging from plagiarism detection to forensics and monitoring the activity of cyber-criminals.
Approach: They propose five new public splits over the PAN dataset to isolate and identify biases related to the text topic and to the author’s writing style.
Outcome: The proposed models are competitive with state-of-the-art methods and generalize better on dark reddit datasets.
DATE: Detecting Anomalies in Text via Self-Supervision of Transformers (2021.naacl-main)

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Challenge: Recent deep learning methods for anomalies in images learn better features of normality in an end-to-end self-supervised setting.
Approach: They propose to use a novel pretext task to learn a deep learning model for Anomaly Detection in text to train a model to discriminate between different transformations applied to visual data.
Outcome: The proposed method outperforms state-of-the-art methods on 20Newsgroups and AG News datasets in the semi-supervised setting and in the unsupervised setting.

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