Update README.md

README.md

@@ -33,3 +33,17 @@ license: apache-2.0
 <p>The curated dataset is pivotal for our investigation into language models' forecasting capabilities, aiming to benchmark against or exceed human predictive performance. It enables focused analysis on high-quality, relevant forecasting questions.</p>
 
 <p>Detailed methodologies and insights from our study are available in the linked paper at the beginning of this document. We invite feedback and collaboration to further this field of research.</p>
+
+<h2>How to Cite</h2>
+<p>If you find our dataset and research useful for your work, please consider citing it using the following BibTeX entry:</p>
+
+```bibtex
+@article{Halawi2024Approaching,
+  title={Approaching Human-Level Forecasting with Language Models},
+  author={Halawi, Danny and Zhang, Fred and Yueh-Han, Chen and Steinhardt, Jacob},
+  journal={arXiv preprint arXiv:2402.18563},
+  year={2024},
+  url={https://arxiv.org/abs/2402.18563},
+  institution={UC Berkeley},
+  email={dhalawi@berkeley.edu, z0@eecs.berkeley.edu, john0922ucb@berkeley.edu, jsteinhardt@berkeley.edu}
+}