Update README.md

README.md

@@ -295,14 +295,18 @@ Despite their remarkable performance based on automatic evaluation metrics, LLMs
 
 However, the evaluators also noted that the final outputs from our models contained more relevant content for Seeds 2 and 3. This observation aligns with the trend in topic consistency scores shown in Auto Evaluation Results for Seed 2 and seed 3, further highlighting the usefulness of ScholaWrite dataset in certain contexts.
 
-## Citation
+## BibTeX
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
+```
+@misc{wang2025scholawritedatasetendtoendscholarly,
+      title={ScholaWrite: A Dataset of End-to-End Scholarly Writing Process},
+      author={Linghe Wang and Minhwa Lee and Ross Volkov and Luan Tuyen Chau and Dongyeop Kang},
+      year={2025},
+      eprint={2502.02904},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2502.02904},
+      }
+```