Papers by Rafael A. Rivera-Soto

1 papers
Learning Universal Authorship Representations (2021.emnlp-main)

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Challenge: authorship verification has traditionally relied on modeling stylometric linguistic properties . but neural methods introduce a tradeoff: they obviate the need for manual feature design .
Approach: They propose to use domain-specific features to improve authorship representations . they propose to study Amazon reviews, fanfiction short stories, and Reddit comments .
Outcome: The proposed methods outperform existing methods in large-scale authorship verification scenarios.

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