He, Yun, Wang, Zhuoer, Zhang, Yin, Huang, Ruihong, and Caverlee, James. PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. Retrieved from https://par.nsf.gov/biblio/10287108. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . Web. doi:10.18653/v1/2020.emnlp-main.611.

He, Yun, Wang, Zhuoer, Zhang, Yin, Huang, Ruihong, & Caverlee, James. PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), (). Retrieved from https://par.nsf.gov/biblio/10287108. https://doi.org/10.18653/v1/2020.emnlp-main.611

He, Yun, Wang, Zhuoer, Zhang, Yin, Huang, Ruihong, and Caverlee, James. "PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge". Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (). Country unknown/Code not available. https://doi.org/10.18653/v1/2020.emnlp-main.611. https://par.nsf.gov/biblio/10287108.

@article{osti_10287108,
place = {Country unknown/Code not available}, title = {PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge}, url = {https://par.nsf.gov/biblio/10287108}, DOI = {10.18653/v1/2020.emnlp-main.611}, abstractNote = {}, journal = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)}, author = {He, Yun and Wang, Zhuoer and Zhang, Yin and Huang, Ruihong and Caverlee, James}, editor = {null} }