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Add ultralytics models publication notice in citations section (#17318)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-11-03 04:54:06 +05:00 • committed by GitHub
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docs/en/models/yolov8.md
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@ -6,10 +6,6 @@ keywords: YOLOv8, real-time object detection, YOLO series, Ultralytics, computer
# Ultralytics YOLOv8
!!! tip "Ultralytics YOLOv8 Publication"
Ultralytics has not published a formal research paper for YOLOv8 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com).
## Overview
YOLOv8 is the latest iteration in the YOLO series of real-time object detectors, offering cutting-edge performance in terms of accuracy and speed. Building upon the advancements of previous YOLO versions, YOLOv8 introduces new features and optimizations that make it an ideal choice for various [object detection](https://www.ultralytics.com/glossary/object-detection) tasks in a wide range of applications.
@ -169,6 +165,10 @@ Note the below example is for YOLOv8 [Detect](../tasks/detect.md) models for obj
## Citations and Acknowledgements
!!! tip "Ultralytics YOLOv8 Publication"
Ultralytics has not published a formal research paper for YOLOv8 due to the rapidly evolving nature of the models. We focus on advancing the technology and making it easier to use, rather than producing static documentation. For the most up-to-date information on YOLO architecture, features, and usage, please refer to our [GitHub repository](https://github.com/ultralytics/ultralytics) and [documentation](https://docs.ultralytics.com).
If you use the YOLOv8 model or any other software from this repository in your work, please cite it using the following format:
!!! quote ""