Paraphrasing with Large Language Models
November 21, 2019 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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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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