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README.md
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@@ -49,3 +49,21 @@ We believe the discrepancies of Rouge-L scores between the original Pegasus work
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| Max | 62.88, [62.42, 63.33] | 43.96, [43.39, 44.54] | 57.50, [57.01, 58.00] |
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| Random | 54.93, [54.43, 55.43] | 35.42, [34.85, 35.97] | 49.19, [48.68, 49.70] |
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| **SimCLS** | 57.49, [57.01, 58.00] | 38.54, [37.98, 39.10] | 51.91, [51.39, 52.43] |
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| Max | 62.88, [62.42, 63.33] | 43.96, [43.39, 44.54] | 57.50, [57.01, 58.00] |
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| Random | 54.93, [54.43, 55.43] | 35.42, [34.85, 35.97] | 49.19, [48.68, 49.70] |
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| **SimCLS** | 57.49, [57.01, 58.00] | 38.54, [37.98, 39.10] | 51.91, [51.39, 52.43] |
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### Citation of the original work
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```bibtex
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@inproceedings{liu-liu-2021-simcls,
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title = "{S}im{CLS}: A Simple Framework for Contrastive Learning of Abstractive Summarization",
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author = "Liu, Yixin and
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Liu, Pengfei",
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booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
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month = aug,
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year = "2021",
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address = "Online",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2021.acl-short.135",
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doi = "10.18653/v1/2021.acl-short.135",
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pages = "1065--1072",
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}
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```
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