update citation (#4)

- update citation (20ee3f3c000e6ecd26d47954d9659bf77c7889e1)

README.md

@@ -195,12 +195,23 @@ All documents originate from the Social Science Open Access Repository (SSOAR) a
 ### Citation Information
 
 ```
-@misc{sv-ident,
-    author={vadis-project},
-    title={SV-Ident},
-    year={2022},
-    url={https://github.com/vadis-project/sv-ident},
-    }
+@inproceedings{tsereteli-etal-2022-overview,
+    title = "Overview of the {SV}-Ident 2022 Shared Task on Survey Variable Identification in Social Science Publications",
+    author = "Tsereteli, Tornike  and
+      Kartal, Yavuz Selim  and
+      Ponzetto, Simone Paolo  and
+      Zielinski, Andrea  and
+      Eckert, Kai  and
+      Mayr, Philipp",
+    booktitle = "Proceedings of the Third Workshop on Scholarly Document Processing",
+    month = oct,
+    year = "2022",
+    address = "Gyeongju, Republic of Korea",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.sdp-1.29",
+    pages = "229--246",
+    abstract = "In this paper, we provide an overview of the SV-Ident shared task as part of the 3rd Workshop on Scholarly Document Processing (SDP) at COLING 2022. In the shared task, participants were provided with a sentence and a vocabulary of variables, and asked to identify which variables, if any, are mentioned in individual sentences from scholarly documents in full text. Two teams made a total of 9 submissions to the shared task leaderboard. While none of the teams improve on the baseline systems, we still draw insights from their submissions. Furthermore, we provide a detailed evaluation. Data and baselines for our shared task are freely available at \url{https://github.com/vadis-project/sv-ident}.",
+}
 ```
 
 ### Contributions