OpenELM arxiv link added

Done on 2024-04-23 based on f7c9720698cd3e5959f39f7fa03310d38729aa3d

README.md

@@ -25,8 +25,7 @@ CoreNet is a deep neural network toolkit that allows researchers and engineers t
 
 Below is the list of publications from Apple that uses CoreNet:
 
-<!-- TODO: add url for OpenELM -->
-   * [OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework]()
+   * [OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework](https://arxiv.org/abs/2404.14619)
 <!-- TODO: add url for CatLIP -->
    * [CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data]()
    * [Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement](https://arxiv.org/abs/2303.08983)

projects/openelm/README.md

@@ -1,5 +1,7 @@
 # OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
 
+[![arXiv](https://img.shields.io/badge/arXiv-2404.14619-a6dba0.svg)](https://arxiv.org/abs/2404.14619)
+
 We provide pretraining, evaluation, instruction tuning, and parameter-efficient finetuning instructions along with pretrained models and checkpoints:
 
 1. [Pre-training](./README-pretraining.md)
@@ -22,13 +24,13 @@ The release of OpenELM models aims to empower and enrich the open research commu
 If you find our work useful, please cite:
 
 ```BibTex 
-# TODO: update OpenELM bibtex
 @article{mehta2024openelm,
   title={OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework},
   author = {Sachin Mehta and Mohammad Hossein Sekhavat and Qingqing Cao and Maxwell Horton and Yanzi Jin and Chenfan Sun and Iman Mirzadeh and Mahyar Najibi and Dmitry Belenko and Peter Zatloukal and Mohammad Rastegari},
   year={2024},
-  journal={},
-  url={},
+  eprint={2404.14619},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL}
 }
 
 @inproceedings{mehta2022cvnets,