docs: mention and link to MLEB

README.md

@@ -66,7 +66,7 @@ This dataset is intended to facilitate the consistent and reproducible evaluatio
 
 More specifically, this dataset tests the ability of information retrieval models to identify legal provisions relevant to US bar exam questions.
 
-This dataset has been processed into the MTEB format by [Isaacus](https://isaacus.com/), a legal AI research company.
+This dataset forms part of the [Massive Legal Embeddings Benchmark (MLEB)](https://isaacus.com/mleb), the largest, most diverse, and most comprehensive benchmark for legal text embedding models. 
 
 ## Methodology 🧪
 To understand how Bar Exam QA was created, refer to its [documentation](https://huggingface.co/datasets/reglab/barexam_qa).
@@ -86,6 +86,7 @@ The `queries` split contains queries, with the text of a query being stored in t
 This dataset is licensed under [CC BY SA 4.0](https://choosealicense.com/licenses/cc-by-sa-4.0/).
 
 ## Citation 🔖
+If you use this dataset, please cite [MLEB](https://isaacus.com/mleb) as well.
 ```bibtex
 @inproceedings{Zheng_2025, series={CSLAW ’25},
    title={A Reasoning-Focused Legal Retrieval Benchmark},
@@ -99,4 +100,12 @@ This dataset is licensed under [CC BY SA 4.0](https://choosealicense.com/license
    collection={CSLAW ’25},
    eprint={2505.03970}
 }
+
+@misc{mleb-2025,
+  title={Massive Legal Embedding Benchmark (MLEB)},
+  author={Umar Butler and Abdur-Rahman Butler},
+  year={2025},
+  url={https://isaacus.com/blog/introducing-mleb},
+  publisher={Isaacus}
+}
 ```