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README.md

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 license: cc-by-2.0
+pretty_name: structure constants of schubert polynomials, n = 4
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 # A Combinatorial Interpretation of Schubert Polynomial Structure Constants
@@ -99,6 +100,37 @@ predict the associated structure constant \\(c^{\gamma}_{\alpha,\beta}\\).
 
 The \\(\pm\\) signs indicate 95% confidence intervals from random weight initialization and training.
 
+- **Curated by:** Henry Kvinge
+- **Funded by:** Pacific Northwest National Laboratory
+- **Language(s) (NLP):** NA
+- **License:** CC-by-2.0
+
+### Dataset Sources
+
+Data generation scripts can be found [here](https://github.com/pnnl/ML4AlgComb/tree/master/schubert_polynomial_structure).
+
+- **Repository:** [ACD Repo](https://github.com/pnnl/ML4AlgComb/tree/master)
+
+## Citation
+
+**BibTeX:**
+
+
+    @article{chau2025machine,
+        title={Machine learning meets algebraic combinatorics: A suite of datasets capturing research-level conjecturing ability in pure mathematics},
+        author={Chau, Herman and Jenne, Helen and Brown, Davis and He, Jesse and Raugas, Mark and Billey, Sara and Kvinge, Henry},
+        journal={arXiv preprint arXiv:2503.06366},
+        year={2025}
+    }
+
+**APA:**
+
+Chau, H., Jenne, H., Brown, D., He, J., Raugas, M., Billey, S., & Kvinge, H. (2025). Machine learning meets algebraic combinatorics: A suite of datasets capturing research-level conjecturing ability in pure mathematics. arXiv preprint arXiv:2503.06366.
+
+## Dataset Card Contact
+
+Henry Kvinge, acdbenchdataset@gmail.com
+
 ## References
 
 \[1\] Bernstein, IMGI N., Israel M. Gel'fand, and Sergei I. Gel'fand. "Schubert cells and cohomology of the spaces G/P." Russian Mathematical Surveys 28.3 (1973): 1.