Update README.md

README.md

@@ -3,4 +3,36 @@ datasets:
 - nilq/babylm-100M
 language:
 - en
----
+---
+
+- GPT-2 model submitted by team CLAUSE Bielefeld to the BabyLM challenge 2023
+- implements a very naive curriculum learning approach inspired by usage-based linguistics: training examples are ordered according to complexity measures from research on child-directed speech (please consult paper for more info)
+
+Citation:
+```
+@inproceedings{bunzeck-zarriess-2023-gpt,
+    title = "{GPT}-wee: How Small Can a Small Language Model Really Get?",
+    author = "Bunzeck, Bastian  and
+      Zarrie{\ss}, Sina",
+    editor = "Warstadt, Alex  and
+      Mueller, Aaron  and
+      Choshen, Leshem  and
+      Wilcox, Ethan  and
+      Zhuang, Chengxu  and
+      Ciro, Juan  and
+      Mosquera, Rafael  and
+      Paranjabe, Bhargavi  and
+      Williams, Adina  and
+      Linzen, Tal  and
+      Cotterell, Ryan",
+    booktitle = "Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning",
+    month = dec,
+    year = "2023",
+    address = "Singapore",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2023.conll-babylm.2",
+    doi = "10.18653/v1/2023.conll-babylm.2",
+    pages = "35--46",
+}
+
+```