Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Paraphrasing with Large Language Models   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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The categories of this paper are: cond-mat
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The categories of this paper are: gr-qc
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The categories of this paper are: math-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-th
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
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The categories of this paper are: comp-gas
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The categories of this paper are: supr-con
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The categories of this paper are: solv-int
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: mtrl-th