Update reference README

README.md

@@ -4,8 +4,8 @@
 This is a RoBERTa-base model trained on 168.86M tweets until the end of September 2022 and finetuned for multi-label topic classification on a corpus of 11,267 [tweets](https://huggingface.co/datasets/cardiffnlp/tweet_topic_multi).
 The original RoBERTa-base model can be found [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-sep2022). This model is suitable for English. 
 
-- Reference Papers: [TimeLMs paper](https://arxiv.org/abs/2202.03829), [TweetTopic](https://arxiv.org/abs/2209.09824) 
-- Git Repo: [TimeLMs official repository](https://github.com/cardiffnlp/timelms).
+ - Reference Paper: [TweetTopic](https://arxiv.org/abs/2209.09824) (COLING 2022). 
+
 
 <b>Labels</b>: 
 
@@ -66,3 +66,26 @@ fitness_&_health
 news_&_social_concern
 sports
 ```
+
+### BibTeX entry and citation info
+
+Please cite the [reference paper](https://aclanthology.org/2022.coling-1.299/) if you use this model.
+
+```bibtex
+@inproceedings{antypas-etal-2022-twitter,
+    title = "{T}witter Topic Classification",
+    author = "Antypas, Dimosthenis  and
+      Ushio, Asahi  and
+      Camacho-Collados, Jose  and
+      Silva, Vitor  and
+      Neves, Leonardo  and
+      Barbieri, Francesco",
+    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
+    month = oct,
+    year = "2022",
+    address = "Gyeongju, Republic of Korea",
+    publisher = "International Committee on Computational Linguistics",
+    url = "https://aclanthology.org/2022.coling-1.299",
+    pages = "3386--3400"
+}
+```