Update README.md

README.md

@@ -103,10 +103,23 @@ As explained in our paper, the dataset is split chronologically for assessing te
 ## Citation
 
 ```
-@article{salaun2024europa,
-  title={EUROPA: A Legal Multilingual Keyphrase Generation Dataset},
-  author={Sala{\"u}n, Olivier and Piedboeuf, Fr{\'e}d{\'e}ric and Le Berre, Guillaume and Hermelo, David Alfonso and Langlais, Philippe},
-  journal={arXiv preprint arXiv:2403.00252},
-  year={2024}
+@inproceedings{salaun-etal-2024-europa,
+    title = "{EUROPA}: A Legal Multilingual Keyphrase Generation Dataset",
+    author = {Sala{\"u}n, Olivier  and
+      Piedboeuf, Fr{\'e}d{\'e}ric  and
+      Le Berre, Guillaume  and
+      Alfonso-Hermelo, David  and
+      Langlais, Philippe},
+    editor = "Ku, Lun-Wei  and
+      Martins, Andre  and
+      Srikumar, Vivek",
+    booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = aug,
+    year = "2024",
+    address = "Bangkok, Thailand",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2024.acl-long.687",
+    pages = "12718--12736",
+    abstract = "Keyphrase generation has primarily been explored within the context of academic research articles, with a particular focus on scientific domains and the English language. In this work, we present EUROPA, a novel dataset for multilingual keyphrase generation in the legal domain. It is derived from legal judgments from the Court of Justice of the European Union (EU), and contains instances in all 24 EU official languages. We run multilingual models on our corpus and analyze the results, showing room for improvement on a domain-specific multilingual corpus such as the one we present.",
 }
 ```