Paraphrasing with Large Language Models

November 21, 2019 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Sam Witteveen, Martin Andrews arXiv ID 1911.09661 Category cs.CL: Computation & Language Cross-listed cs.LG Citations 90 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 4 months ago
Abstract
Recently, large language models such as GPT-2 have shown themselves to be extremely adept at text generation and have also been able to achieve high-quality results in many downstream NLP tasks such as text classification, sentiment analysis and question answering with the aid of fine-tuning. We present a useful technique for using a large language model to perform the task of paraphrasing on a variety of texts and subjects. Our approach is demonstrated to be capable of generating paraphrases not only at a sentence level but also for longer spans of text such as paragraphs without needing to break the text into smaller chunks.
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