Update README.md

README.md

@@ -11,14 +11,16 @@ This model is initialized with the base BERT model (uncased, 110M parameters), [
 Please see the [casehold repository](https://github.com/reglab/casehold) for scripts that support computing pretrain loss and finetuning on Legal-BERT for classification and multiple choice tasks described in the paper: Overruling, Terms of Service, CaseHOLD.
 
 ### Citation
-\t@inproceedings{zhengguha2021,
-\t\ttitle={When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset},
-\t\tauthor={Lucia Zheng and Neel Guha and Brandon R. Anderson and Peter Henderson and Daniel E. Ho},
-\t\tyear={2021},
-\t\teprint={2104.08671},
-\t\tarchivePrefix={arXiv},
-\t\tprimaryClass={cs.CL},
-\t\tbooktitle={Proceedings of the 18th International Conference on Artificial Intelligence and Law},
-\t\tpublisher={Association for Computing Machinery},
-\t\tnote={(in press)}
-\t}
+```
+@inproceedings{zhengguha2021,
+		title={When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset},
+		author={Lucia Zheng and Neel Guha and Brandon R. Anderson and Peter Henderson and Daniel E. Ho},
+		year={2021},
+		eprint={2104.08671},
+		archivePrefix={arXiv},
+		primaryClass={cs.CL},
+		booktitle={Proceedings of the 18th International Conference on Artificial Intelligence and Law},
+		publisher={Association for Computing Machinery},
+		note={(in press)}
+}
+```