Update README.md

README.md

@@ -11,17 +11,30 @@ library_name: transformers
 
 ## Model Sources
 
-- **Repository:** [https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT](https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT)
-- **Paper:** [SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models](https://arxiv.org/abs/2410.03750)
+**Repository:** [https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT](https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT)
+
+**Paper:**
+- [SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models](https://arxiv.org/abs/2410.03750)
+- [Low-Rank Adapters Meet Neural Architecture Search for LLM Compression](https://arxiv.org/abs/2501.16372)
 
 ## Citation
 
 ```bash
-@article{munoz2024sqft,
-  title = {SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models},
-  author={J. Pablo Munoz and Jinjie Yuan and Nilesh Jain},
-  journal={The 2024 Conference on Empirical Methods in Natural Language Processing (Findings)},
-  year={2024}
+@inproceedings{munoz-etal-2024-sqft,
+    title = "{SQFT}: Low-cost Model Adaptation in Low-precision Sparse Foundation Models",
+    author = "Munoz, Juan Pablo  and
+      Yuan, Jinjie  and
+      Jain, Nilesh",
+    editor = "Al-Onaizan, Yaser  and
+      Bansal, Mohit  and
+      Chen, Yun-Nung",
+    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
+    month = nov,
+    year = "2024",
+    address = "Miami, Florida, USA",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2024.findings-emnlp.749",
+    pages = "12817--12832",
 }
 ```