Added Usage, Citation, and Contact info to the ReadMe

README.md

@@ -47,6 +47,36 @@ The MultiSim benchmark is a growing collection of text simplification datasets t
 
 - Sentence Simplification
 
+### Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("MichaelR207/MultiSim")
+```
+
+### Citation
+```
+@inproceedings{ryan-etal-2023-revisiting,
+    title = "Revisiting non-{E}nglish Text Simplification: A Unified Multilingual Benchmark",
+    author = "Ryan, Michael  and
+      Naous, Tarek  and
+      Xu, Wei",
+    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = jul,
+    year = "2023",
+    address = "Toronto, Canada",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2023.acl-long.269",
+    pages = "4898--4927",
+    abstract = "Recent advancements in high-quality, large-scale English resources have pushed the frontier of English Automatic Text Simplification (ATS) research. However, less work has been done on multilingual text simplification due to the lack of a diverse evaluation benchmark that covers complex-simple sentence pairs in many languages. This paper introduces the MultiSim benchmark, a collection of 27 resources in 12 distinct languages containing over 1.7 million complex-simple sentence pairs. This benchmark will encourage research in developing more effective multilingual text simplification models and evaluation metrics. Our experiments using MultiSim with pre-trained multilingual language models reveal exciting performance improvements from multilingual training in non-English settings. We observe strong performance from Russian in zero-shot cross-lingual transfer to low-resource languages. We further show that few-shot prompting with BLOOM-176b achieves comparable quality to reference simplifications outperforming fine-tuned models in most languages. We validate these findings through human evaluation.",
+}
+```
+
+### Contact
+
+**Michael Ryan**: [Scholar](https://scholar.google.com/citations?user=8APGEEkAAAAJ&hl=en) | [Twitter](http://twitter.com/michaelryan207) | [Github](https://github.com/XenonMolecule) | [LinkedIn](https://www.linkedin.com/in/michael-ryan-207/) | [Research Gate](https://www.researchgate.net/profile/Michael-Ryan-86) | [Personal Website](http://michaelryan.tech/) | [[email protected]](mailto://[email protected])
+
 ### Languages
 
 - English
@@ -165,6 +195,8 @@ MIT License
 
 ### Citation Information
 
+Please cite the individual datasets that you use within the MultiSim benchmark as appropriate. Proper bibtex attributions for each of the datasets are included below.
+
 #### AdminIT
 ```
 @inproceedings{miliani-etal-2022-neural,