Added reference to paper.

README.md

@@ -169,6 +169,9 @@ development of models capable of generating syntactically correct and
 semantically meaningful Coq constructs, thereby advancing automated
 theorem proving.
 
+A detailed description can be found in the paper
+[Enhancing Formal Theorem Proving: A Comprehensive Dataset for Training AI Models on Coq Code](https://arxiv.org/abs/2403.12627).
+
 ## Composition
 
 * Files: Over 10,000 Coq source files (`.v` files).
@@ -244,6 +247,19 @@ specialized model training for formal theorem proving.
 * The complexity of licensing and the manual process of license
   identification for each repository.
 
+## Cite
+
+```
+@misc{florath2024enhancing,
+      title={Enhancing Formal Theorem Proving: A Comprehensive Dataset for Training AI Models on Coq Code}, 
+      author={Andreas Florath},
+      year={2024},
+      eprint={2403.12627},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI}
+}
+```
+
 ## Legal Disclaimer
 This dataset is provided 'as is' and without any warranty or guarantee of
 accuracy, completeness, or compliance with any specific legal regime.  While