Update date in README.md (#13)

Author: Quentin-Anthony

README.md

@@ -3,7 +3,7 @@
 MCR-DL is a [HiDL](https://hidl.cse.ohio-state.edu/) project. We encourage you to visit the [HiDL website](https://hidl.cse.ohio-state.edu/) for additional information, the latest performance numbers, and similar projects on high-performance machine and deep learning. For the latest announcements on HiDL projects, [register for the HiDL mailing list](https://hidl.cse.ohio-state.edu/mailinglists/).
 
 # News
-**[12/XXX/2023]** The initial release of MCR-DL! For now, we only support basic single-backend communication without going through the PyTorch distributed module. For a full list of new and existing features, please see [the MCR-DL feature page](http://hidl.cse.ohio-state.edu/features/#MCR-DL)
+**[12/24/2023]** The initial release of MCR-DL! For now, we only support basic single-backend communication without going through the PyTorch distributed module. For a full list of new and existing features, please see [the MCR-DL feature page](http://hidl.cse.ohio-state.edu/features/#MCR-DL)
 
 # MCR-DL v0.1
 
@@ -90,4 +90,4 @@ To add new communication benchmarks, follow this general procedure:
 
 
 ## References
-1. Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar Panda. (2023) MCR-DL: Mix-and-Match Communication Runtime for Deep Learning [arXiv:2303.08374](https://arxiv.org/abs/2303.08374) and will appear at IPDPS 2023.
+1. Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar Panda. (2023) MCR-DL: Mix-and-Match Communication Runtime for Deep Learning [arXiv:2303.08374](https://arxiv.org/abs/2303.08374) and will appear at IPDPS 2023.