Update README.md

README.md

@@ -34,6 +34,8 @@ For this reason, we produce two versions of the variances:
 1. **Approximation Variances**: These are approximations to the full GloVe-V variances that can use either a diagonal approximation to the full variance, or a low-rank Singular Value Decomposition (SVD) approximation. We optimize this approximation at the level of each word to guarantee at least 90% reconstruction of the original variance. These approximations require storing much fewer floating point numbers than the full variances.
 2. **Complete Variances**: These are the full GloVe-V variances, which require storing $V \times (D x D)$ floating point numbers. For example, in the case of the 300-dimensional embeddings for the COHA (1900-1999) corpus, this would be approximately 6.4 billion floating point numbers!
 
+- **Created By:** Andrea Vallebueno, Cassandra Handan-Nader, Christopher D. Manning, and Daniel E. Ho
+- **Languages:** English
 - **License:** The license of these data products varies according to each corpora. In the case of the COHA corpus, these data products are intended for academic use only.
 
 ### Dataset Sources