Update README.md

README.md

@@ -48,7 +48,7 @@ model = AutoModel.from_pretrained("nlpaueb/sec-bert-base")
 
 ## Pre-process Text
 
-To use SEC-BERT-SHAPE, you have to pre-process texts replacing every numerical token with the corresponding shape pseudo-token, from a list of 214 predefined shape pseudo-tokens. If the numerical token does not correspond to any shape pseudo token we replace it with the [NUM] pseudo-token.
+To use SEC-BERT-SHAPE, you have to pre-process texts replacing every numerical token with the corresponding shape pseudo-token, from a list of 214 predefined shape pseudo-tokens. If the numerical token does not correspond to any shape pseudo-token we replace it with the [NUM] pseudo-token.
 Below there is an example of how you can pre-process a simple sentence. This approach is quite simple; feel free to modify it as you see fit.
 
 ```python
@@ -84,7 +84,7 @@ print(tokenized_sentence)
 """
 ```
 
-## Use SEC-BERT variants as Language Models
+## Using SEC-BERT variants as Language Models
 
 | Sample                                              | Masked Token |
 | --------------------------------------------------- | ------------ |
@@ -224,6 +224,23 @@ The model has been officially released with the following article:<br>
 Lefteris Loukas, Manos Fergadiotis, Ilias Chalkidis, Eirini Spyropoulou, Prodromos Malakasiotis, Ion Androutsopoulos and George Paliouras.<br>
 In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022.
 
+```
+@inproceedings{loukas-etal-2022-finer,
+    title = "{FiNER: Financial Numeric Entity Recognition for XBRL Tagging}",
+    author = "Loukas, Lefteris  and
+      Fergadiotis, Manos  and
+      Chalkidis, Ilias and
+      Spyropoulou, Eirini and
+      Malakasiotis, Prodromos  and
+      Androutsopoulos, Ion and
+      Paliouras George",
+    booktitle = "60th Annual Meeting of the Association for Computational Linguistics",
+    month = may,
+    year = "2022",
+    publisher = "Association for Computational Linguistics",
+}
+```
+
 ## About Us
 
 [AUEB's Natural Language Processing Group](http://nlp.cs.aueb.gr) develops algorithms, models, and systems that allow computers to process and generate natural language texts.