Update README.md

README.md

@@ -39,4 +39,22 @@ We provide the results of the model on our proposed benchmarks in this table:
 
 In essence, while we hope that ViSPer will open the doors for new research questions and opportunities, and should only be used for this purpose. There are also potential dual use concerns that come with releasing ViSPer (dataset and models), trained on a substantial corpus of multilingual video data. While the technology behind ViSPer offers significant advances in multiomodal speech recognition, its should only be used for research purposes.
 
-
+## Citation
+```bash
+
+@inproceedings{djilali2023lip2vec,
+  title={Lip2Vec: Efficient and Robust Visual Speech Recognition via Latent-to-Latent Visual to Audio Representation Mapping},
+  author={Djilali, Yasser Abdelaziz Dahou and Narayan, Sanath and Boussaid, Haithem and Almazrouei, Ebtessam and Debbah, Merouane},
+  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
+  pages={13790--13801},
+  year={2023}
+}
+
+@inproceedings{djilali2024vsr,
+  title={Do VSR Models Generalize Beyond LRS3?},
+  author={Djilali, Yasser Abdelaziz Dahou and Narayan, Sanath and LeBihan, Eustache and Boussaid, Haithem and Almazrouei, Ebtesam and Debbah, Merouane},
+  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
+  pages={6635--6644},
+  year={2024}
+}
+```