Papers by Katarzyna Beksa

1 papers
An Empirical Study on Multi-Task Learning for Text Style Transfer and Paraphrase Generation (2020.coling-industry)

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Challenge: a limited amount of style data is needed for text style transfer, but there are no convincing methods for evaluating them.
Approach: They propose an efficient method for neutral-to-style transformation using the transformer framework.
Outcome: The proposed method can train neutral-to-style transformation models using large paraphrases and a small style transfer corpus.

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