  We propose ParaSCI, the first large-scale paraphrase dataset in the
scientific field, including 33,981 paraphrase pairs from ACL (ParaSCI-ACL) and
316,063 pairs from arXiv (ParaSCI-arXiv). Digging into characteristics and
common patterns of scientific papers, we construct this dataset though
intra-paper and inter-paper methods, such as collecting citations to the same
paper or aggregating definitions by scientific terms. To take advantage of
sentences paraphrased partially, we put up PDBERT as a general paraphrase
discovering method. The major advantages of paraphrases in ParaSCI lie in the
prominent length and textual diversity, which is complementary to existing
paraphrase datasets. ParaSCI obtains satisfactory results on human evaluation
and downstream tasks, especially long paraphrase generation.
