docs: mention and link to MLEB

README.md

@@ -75,7 +75,7 @@ Uniquely, this dataset sources its real-life tax questions from the posts of eve
 
 The fact that questions center around substantive and often complex tax problems, which are broadly representative of the problems faced by everyday Australian taxpayers, makes this dataset extremely valuable for the robust evaluation of the legal retrieval capabilities and tax domain understanding of information retrieval models.
 
-To make evaluation with this dataset as easy as possible, it is formatted in the [Massive Text Embedding Benchmark (MTEB)](https://github.com/embeddings-benchmark/mteb) information retrieval dataset format.
+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. 
 
 ## Structure 🗂️
 As per the MTEB information retrieval dataset format, this dataset comprises three splits, `default`, `corpus` and `queries`.
@@ -99,6 +99,7 @@ This dataset was constructed by:
 This dataset is licensed under [CC BY 4.0](https://choosealicense.com/licenses/cc-by-4.0/) which allows for both non-commercial and commercial use of this dataset as long as appropriate attribution is made to it.
 
 ## Citation 🔖
+If you use this dataset, please cite [MLEB](https://isaacus.com/mleb) as well.
 ```bibtex
 @misc{butler-2025-australian-tax-guidance-retrieval,
     author = {Butler, Abdur-Rahman and Butler, Umar},
@@ -108,4 +109,12 @@ This dataset is licensed under [CC BY 4.0](https://choosealicense.com/licenses/c
     version = {0.1.0},
     url = {https://huggingface.co/datasets/isaacus/australian-tax-guidance-retrieval}
 }
+
+@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}
+}
 ```