Update README.md

README.md

@@ -14,4 +14,19 @@ This is the JobSpanBERT model from:
 
 Mike Zhang, Kristian Nørgaard Jensen, Sif Dam Sonniks, and Barbara Plank. __SkillSpan: Hard and Soft Skill Extraction from Job Postings__. To appear at the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). 2022.
 
-This model is continuously pre-trained from a spanbert-base-cased checkpoint (which can also be found in our repository) on ~3.2M sentences from job postings. More information can be found in the paper (which should be released when the NAACL proceedings are online).
+This model is continuously pre-trained from a spanbert-base-cased checkpoint (which can also be found in our repository) on ~3.2M sentences from job postings. More information can be found in the paper (which should be released when the NAACL proceedings are online).
+
+If you use this model, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.12811,
+      doi = {10.48550/ARXIV.2204.12811},
+      url = {https://arxiv.org/abs/2204.12811},
+      author = {Zhang, Mike and Jensen, Kristian Nørgaard and Sonniks, Sif Dam and Plank, Barbara},
+      keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
+      title = {SkillSpan: Hard and Soft Skill Extraction from English Job Postings},
+      publisher = {arXiv},
+      year = {2022},
+      copyright = {arXiv.org perpetual, non-exclusive license}
+}
+```