Year: 2019
Type: conference-paper
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.
DOI: 10.18653/v1/d19-5623
Authors: Sam Witteveen, Martin Andrews
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2990191328