Update README.md

README.md

@@ -46,3 +46,32 @@ configs:
   - split: test
     path: data/test-*
 ---
+This dataset is a modified version of the HotPotQA distractor dataset, which contains factual questions requiring multi-hop reasoning. 
+In the original HotPotQA dataset, each example presents ten paragraphs, only two of which contain the information necessary to answer the question; the remaining eight paragraphs include closely related but irrelevant details. 
+Consequently, solving this task requires the model to identify and reason over the pertinent passages.
+To more strongly develop uncertainty reasoning capability, we construct \textit{HotPotQA-Modified}, in which we systematically remove either 0, 1, or both of the key paragraphs required to answer each question. 
+This modification introduces varying levels of informational completeness that the model must reason over. 
+The "gold_removed" column indicates the number of relevant paragraphs removed (0,1 or 2).
+Questions are distributed across three equal groups: one-third have no relevant paragraphs (0/8), one-third have 1 relevant paragraph (1/7), and one-third have both relevant paragraphs (2/6). Each question consistently contains 8 total paragraphs.
+
+To cite the original HotPotQA dataset: 
+```bibtex
+@article{yang2018hotpotqa,
+  title={HotpotQA: A dataset for diverse, explainable multi-hop question answering},
+  author={Yang, Zhilin and Qi, Peng and Zhang, Saizheng and Bengio, Yoshua and Cohen, William W and Salakhutdinov, Ruslan and Manning, Christopher D},
+  journal={arXiv preprint arXiv:1809.09600},
+  year={2018}
+}
+```
+
+To cite our modified dataset:
+
+```bibtex
+@article{damani2025beyond,
+  title={Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty},
+  author={Damani, Mehul and Puri, Isha and Slocum, Stewart and Shenfeld, Idan and Choshen, Leshem and Kim, Yoon and Andreas, Jacob},
+  journal={arXiv preprint arXiv:2507.16806},
+  year={2025}
+}
+```
+