📝 [Update] doc!

README.md

@@ -1,4 +1,4 @@
-# YOLO: Official Implementation of YOLOv9, YOLOv7
+# YOLO: Official Implementation of YOLOv9, YOLOv7, YOLO-RD
 
 [![Documentation Status](https://readthedocs.org/projects/yolo-docs/badge/?version=latest)](https://yolo-docs.readthedocs.io/en/latest/?badge=latest)
 ![GitHub License](https://img.shields.io/github/license/WongKinYiu/YOLO)
@@ -17,7 +17,7 @@
 >
 > Use of this code is at your own risk and discretion. It is advisable to consult with the project owner before deploying or integrating into any critical systems. -->
 
-Welcome to the official implementation of YOLOv7 and YOLOv9. This repository will contains the complete codebase, pre-trained models, and detailed instructions for training and deploying YOLOv9.
+Welcome to the official implementation of YOLOv7 and YOLOv9, YOLO-RD. This repository will contains the complete codebase, pre-trained models, and detailed instructions for training and deploying YOLOv9.
 
 ## TL;DR
 
@@ -33,6 +33,7 @@ yolo task.data.source=0 # source could be a single file, video, image folder, we
 
 - [**YOLOv9**: Learning What You Want to Learn Using Programmable Gradient Information](https://arxiv.org/abs/2402.13616)
 - [**YOLOv7**: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors](https://arxiv.org/abs/2207.02696)
+- [**YOLO-RD**: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary](https://arxiv.org/abs/2410.15346)
 
 ## Installation
 
@@ -111,20 +112,24 @@ Contributions to the YOLO project are welcome! See [CONTRIBUTING](docs/CONTRIBUT
 ## Citations
 
 ```
-@misc{wang2022yolov7,
-      title={YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
-      author={Chien-Yao Wang and Alexey Bochkovskiy and Hong-Yuan Mark Liao},
-      year={2022},
-      eprint={2207.02696},
-      archivePrefix={arXiv},
-      primaryClass={id='cs.CV' full_name='Computer Vision and Pattern Recognition' is_active=True alt_name=None in_archive='cs' is_general=False description='Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.'}
+@inproceedings{wang2022yolov7,
+      title={{YOLOv7}: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors},
+      author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
+      year={2023},
+      booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+
 }
-@misc{wang2024yolov9,
-      title={YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information},
-      author={Chien-Yao Wang and I-Hau Yeh and Hong-Yuan Mark Liao},
+@inproceedings{wang2024yolov9,
+      title={{YOLOv9}: Learning What You Want to Learn Using Programmable Gradient Information},
+      author={Wang, Chien-Yao and Yeh, I-Hau and Liao, Hong-Yuan Mark},
       year={2024},
-      eprint={2402.13616},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV}
+      booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
+}
+@inproceedings{tsui2024yolord,
+      author = {Tsui, Hao-Tang and Wang, Chien-Yao and Liao, Hong-Yuan Mark},
+      title = {YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary},
+      booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
+      year = {2025},
 }
+
 ```