Papers with similarity-based models

2 papers
Large Scale Author Obfuscation Using Siamese Variational Auto-Encoder: The SiamAO System (2020.starsem-1)

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Challenge: Existing approaches to author obfuscation are largely heuristic, but they can be used to attack author identification.
Approach: They propose a deep learning architecture for constructing adversarial examples against similarity-based learners and explore its application to author obfuscation.
Outcome: The proposed architectures show that they can be used to attack author obfuscation . the proposed architecture shows that it can be applied to obliquacy of text .
Similarity or deeper understanding? Analyzing the TED-Q dataset of evoked questions (2020.coling-main)

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Challenge: TED-Q datasets are annotated with the questions they implicitly evoke, based on a dataset of TED talks . we test whether relation between a discourse and questions it evokes is one of similarity or association .
Approach: They construct a binary classification task from TED-Q and fit a BERT-based classifier alongside models based on different notions of similarity.
Outcome: The proposed classifier outperforms similarity-based models in the TED-Q dataset.

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