ultralytics · onuralpszr · Apr 30, 2026
diff --git a/docs/en/compare/damo-yolo-vs-efficientdet.md b/docs/en/compare/damo-yolo-vs-efficientdet.md
@@ -11,7 +11,7 @@ The evolution of computer vision has produced an array of powerful architectures
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "EfficientDet"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "EfficientDet"&#93;'></canvas>
 
 ## Architectural Overview
 

diff --git a/docs/en/compare/damo-yolo-vs-pp-yoloe.md b/docs/en/compare/damo-yolo-vs-pp-yoloe.md
@@ -11,7 +11,7 @@ In the highly competitive landscape of real-time computer vision, choosing the o
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "PP-YOLOE+"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "PP-YOLOE+"&#93;'></canvas>
 
 ## Model Overviews
 

diff --git a/docs/en/compare/damo-yolo-vs-rtdetr.md b/docs/en/compare/damo-yolo-vs-rtdetr.md
@@ -11,7 +11,7 @@ The rapidly evolving landscape of computer vision has produced an impressive arr
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "RTDETRv2"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "RTDETRv2"&#93;'></canvas>
 
 This comprehensive guide dives deep into the technical specifications, architectural innovations, and practical use cases of both models, while also exploring how modern solutions like the [Ultralytics Platform](https://platform.ultralytics.com) and the state-of-the-art [YOLO26](https://platform.ultralytics.com/ultralytics/yolo26) have redefined industry standards for deployment and ease of use.
 

diff --git a/docs/en/compare/damo-yolo-vs-yolo11.md b/docs/en/compare/damo-yolo-vs-yolo11.md
@@ -26,7 +26,7 @@ Docs: [YOLO11 Documentation](https://docs.ultralytics.com/models/yolo11/)
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLO11"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLO11"&#93;'></canvas>
 
 ## Architectural Design Philosophy
 

diff --git a/docs/en/compare/damo-yolo-vs-yolo26.md b/docs/en/compare/damo-yolo-vs-yolo26.md
@@ -13,7 +13,7 @@ Whether you are deploying vision models to edge devices or building high-through
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLO26"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLO26"&#93;'></canvas>
 
 ## DAMO-YOLO: Neural Architecture Search at Scale
 

diff --git a/docs/en/compare/damo-yolo-vs-yolov10.md b/docs/en/compare/damo-yolo-vs-yolov10.md
@@ -11,7 +11,7 @@ The field of computer vision has witnessed a rapid evolution in real-time [objec
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOv10"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOv10"&#93;'></canvas>
 
 ## DAMO-YOLO: Neural Architecture Search at Scale
 

diff --git a/docs/en/compare/damo-yolo-vs-yolov5.md b/docs/en/compare/damo-yolo-vs-yolov5.md
@@ -11,7 +11,7 @@ The evolution of [computer vision](https://www.ultralytics.com/glossary/computer
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOv5"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOv5"&#93;'></canvas>
 
 ## Introduction to DAMO-YOLO
 

diff --git a/docs/en/compare/damo-yolo-vs-yolov6.md b/docs/en/compare/damo-yolo-vs-yolov6.md
@@ -11,7 +11,7 @@ The rapid evolution of computer vision has produced highly specialized architect
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOv6-3.0"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOv6-3.0"&#93;'></canvas>
 
 ## DAMO-YOLO: Neural Architecture Search Meets Object Detection
 

diff --git a/docs/en/compare/damo-yolo-vs-yolov7.md b/docs/en/compare/damo-yolo-vs-yolov7.md
@@ -13,7 +13,7 @@ This comprehensive technical comparison explores the distinct approaches of both
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOv7"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOv7"&#93;'></canvas>
 
 ## Model Origins and Metadata
 

diff --git a/docs/en/compare/damo-yolo-vs-yolov8.md b/docs/en/compare/damo-yolo-vs-yolov8.md
@@ -13,7 +13,7 @@ This comprehensive technical breakdown will compare their underlying architectur
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOv8"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOv8"&#93;'></canvas>
 
 ## Model Lineage and Specifications
 

diff --git a/docs/en/compare/damo-yolo-vs-yolov9.md b/docs/en/compare/damo-yolo-vs-yolov9.md
@@ -13,7 +13,7 @@ This detailed technical guide provides an in-depth analysis of these two models,
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOv9"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOv9"&#93;'></canvas>
 
 ## Executive Summary: Choosing the Right Architecture
 

diff --git a/docs/en/compare/damo-yolo-vs-yolox.md b/docs/en/compare/damo-yolo-vs-yolox.md
@@ -11,7 +11,7 @@ The landscape of real-time computer vision is constantly evolving. Two notable m
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["DAMO-YOLO", "YOLOX"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"DAMO-YOLO", "YOLOX"&#93;'></canvas>
 
 This comprehensive guide explores the technical nuances of both models and highlights why modern alternatives like the [Ultralytics YOLO26](https://platform.ultralytics.com/ultralytics/yolo26) platform offer superior performance and ease of use for today's production environments.
 

diff --git a/docs/en/compare/efficientdet-vs-damo-yolo.md b/docs/en/compare/efficientdet-vs-damo-yolo.md
@@ -13,7 +13,7 @@ While both models brought significant innovations to the field of [object detect
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "DAMO-YOLO"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "DAMO-YOLO"&#93;'></canvas>
 
 ## EfficientDet: Scalable and Efficient Object Detection
 

diff --git a/docs/en/compare/efficientdet-vs-pp-yoloe.md b/docs/en/compare/efficientdet-vs-pp-yoloe.md
@@ -13,7 +13,7 @@ This comprehensive guide dissects their architectures, training methodologies, a
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "PP-YOLOE+"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "PP-YOLOE+"&#93;'></canvas>
 
 ## Architectural Innovations and Design Philosophies
 

diff --git a/docs/en/compare/efficientdet-vs-rtdetr.md b/docs/en/compare/efficientdet-vs-rtdetr.md
@@ -13,7 +13,7 @@ By understanding the trade-offs between legacy efficiency and modern transformer
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "RTDETRv2"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "RTDETRv2"&#93;'></canvas>
 
 ## Understanding EfficientDet
 

diff --git a/docs/en/compare/efficientdet-vs-yolo11.md b/docs/en/compare/efficientdet-vs-yolo11.md
@@ -13,7 +13,7 @@ Whether you are targeting millisecond latency on [edge AI](https://www.ultralyti
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLO11"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLO11"&#93;'></canvas>
 
 ## Model Profiles and Technical Details
 

diff --git a/docs/en/compare/efficientdet-vs-yolo26.md b/docs/en/compare/efficientdet-vs-yolo26.md
@@ -32,7 +32,7 @@ GitHub: [ultralytics/ultralytics](https://github.com/ultralytics/ultralytics)
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLO26"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLO26"&#93;'></canvas>
 
 ## Architectural Innovations
 

diff --git a/docs/en/compare/efficientdet-vs-yolov10.md b/docs/en/compare/efficientdet-vs-yolov10.md
@@ -13,7 +13,7 @@ We will explore their core architectures, review performance benchmarks on [stan
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOv10"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOv10"&#93;'></canvas>
 
 ## EfficientDet: The Compound Scaling Pioneer
 

diff --git a/docs/en/compare/efficientdet-vs-yolov5.md b/docs/en/compare/efficientdet-vs-yolov5.md
@@ -13,7 +13,7 @@ By comparing their architectural innovations, training methodologies, and deploy
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOv5"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOv5"&#93;'></canvas>
 
 ## EfficientDet: Scalable Architecture with BiFPN
 

diff --git a/docs/en/compare/efficientdet-vs-yolov6.md b/docs/en/compare/efficientdet-vs-yolov6.md
@@ -13,7 +13,7 @@ While both architectures represented major leaps forward upon their respective r
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOv6-3.0"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOv6-3.0"&#93;'></canvas>
 
 ## EfficientDet: Scalable AutoML Architecture
 

diff --git a/docs/en/compare/efficientdet-vs-yolov7.md b/docs/en/compare/efficientdet-vs-yolov7.md
@@ -13,7 +13,7 @@ This comprehensive technical analysis explores the architectural nuances, [perfo
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOv7"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOv7"&#93;'></canvas>
 
 ## Understanding EfficientDet
 

diff --git a/docs/en/compare/efficientdet-vs-yolov8.md b/docs/en/compare/efficientdet-vs-yolov8.md
@@ -13,7 +13,7 @@ Whether your goal is deploying models on highly constrained [edge computing](htt
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOv8"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOv8"&#93;'></canvas>
 
 ## Model Overview and Origins
 

diff --git a/docs/en/compare/efficientdet-vs-yolov9.md b/docs/en/compare/efficientdet-vs-yolov9.md
@@ -13,7 +13,7 @@ This guide provides a comprehensive technical comparison between these two model
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOv9"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOv9"&#93;'></canvas>
 
 ## Model Architectures and Innovations
 

diff --git a/docs/en/compare/efficientdet-vs-yolox.md b/docs/en/compare/efficientdet-vs-yolox.md
@@ -11,7 +11,7 @@ When architecting a modern [computer vision](https://www.ultralytics.com/glossar
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["EfficientDet", "YOLOX"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"EfficientDet", "YOLOX"&#93;'></canvas>
 
 ## EfficientDet Overview
 

diff --git a/docs/en/compare/pp-yoloe-vs-damo-yolo.md b/docs/en/compare/pp-yoloe-vs-damo-yolo.md
@@ -13,7 +13,7 @@ This guide provides a detailed technical analysis of PP-YOLOE+ and DAMO-YOLO, ex
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "DAMO-YOLO"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "DAMO-YOLO"&#93;'></canvas>
 
 ## PP-YOLOE+: Refined Industrial Object Detection
 

diff --git a/docs/en/compare/pp-yoloe-vs-efficientdet.md b/docs/en/compare/pp-yoloe-vs-efficientdet.md
@@ -13,7 +13,7 @@ While both models have made significant contributions to the field, we will also
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "EfficientDet"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "EfficientDet"&#93;'></canvas>
 
 ## Architectural Overview: PP-YOLOE+
 

diff --git a/docs/en/compare/pp-yoloe-vs-rtdetr.md b/docs/en/compare/pp-yoloe-vs-rtdetr.md
@@ -11,7 +11,7 @@ The field of computer vision has witnessed a dramatic evolution in recent years,
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "RTDETRv2"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "RTDETRv2"&#93;'></canvas>
 
 ## PP-YOLOE+: Advancing the CNN Paradigm
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolo11.md b/docs/en/compare/pp-yoloe-vs-yolo11.md
@@ -13,7 +13,7 @@ By dissecting their architectures, performance metrics, and ideal use cases, thi
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLO11"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLO11"&#93;'></canvas>
 
 ## Model Origins and Technical Overviews
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolo26.md b/docs/en/compare/pp-yoloe-vs-yolo26.md
@@ -13,7 +13,7 @@ This comprehensive guide compares these two models, highlighting their architect
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLO26"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLO26"&#93;'></canvas>
 
 ## Technical Specifications and Authorship
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolov10.md b/docs/en/compare/pp-yoloe-vs-yolov10.md
@@ -11,7 +11,7 @@ The landscape of computer vision is constantly evolving, with new models pushing
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOv10"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOv10"&#93;'></canvas>
 
 ## Introduction to the Models
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolov5.md b/docs/en/compare/pp-yoloe-vs-yolov5.md
@@ -11,7 +11,7 @@ When choosing the right deep learning framework for computer vision, developers
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOv5"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOv5"&#93;'></canvas>
 
 ## Model Origins and Metadata
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolov6.md b/docs/en/compare/pp-yoloe-vs-yolov6.md
@@ -13,7 +13,7 @@ Before diving into the detailed architectural breakdowns, explore the chart belo
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOv6-3.0"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOv6-3.0"&#93;'></canvas>
 
 ## PP-YOLOE+: Architectural Strengths and Weaknesses
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolov7.md b/docs/en/compare/pp-yoloe-vs-yolov7.md
@@ -11,7 +11,7 @@ When building computer vision pipelines, selecting the right object detection mo
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOv7"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOv7"&#93;'></canvas>
 
 ## Overview of the Models
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolov8.md b/docs/en/compare/pp-yoloe-vs-yolov8.md
@@ -11,7 +11,7 @@ The demand for high-performance, real-time [computer vision](https://en.wikipedi
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOv8"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOv8"&#93;'></canvas>
 
 ## Introduction to the Architectures
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolov9.md b/docs/en/compare/pp-yoloe-vs-yolov9.md
@@ -13,7 +13,7 @@ This comprehensive technical comparison analyzes their architectural innovations
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOv9"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOv9"&#93;'></canvas>
 
 ## Model Lineage and Technical Foundations
 

diff --git a/docs/en/compare/pp-yoloe-vs-yolox.md b/docs/en/compare/pp-yoloe-vs-yolox.md
@@ -11,7 +11,7 @@ The landscape of [computer vision](https://www.ultralytics.com/glossary/computer
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["PP-YOLOE+", "YOLOX"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"PP-YOLOE+", "YOLOX"&#93;'></canvas>
 
 ## Model Lineage and Details
 

diff --git a/docs/en/compare/rtdetr-vs-damo-yolo.md b/docs/en/compare/rtdetr-vs-damo-yolo.md
@@ -13,7 +13,7 @@ In this technical comparison, we will dive deep into their architectures, traini
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["RTDETRv2", "DAMO-YOLO"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"RTDETRv2", "DAMO-YOLO"&#93;'></canvas>
 
 ## Architectural Innovations
 

diff --git a/docs/en/compare/rtdetr-vs-efficientdet.md b/docs/en/compare/rtdetr-vs-efficientdet.md
@@ -11,7 +11,7 @@ Selecting the optimal neural network architecture is a defining choice for any [
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["RTDETRv2", "EfficientDet"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"RTDETRv2", "EfficientDet"&#93;'></canvas>
 
 ## RTDETRv2: The Real-Time Detection Transformer
 

diff --git a/docs/en/compare/rtdetr-vs-pp-yoloe.md b/docs/en/compare/rtdetr-vs-pp-yoloe.md
@@ -13,7 +13,7 @@ This comprehensive guide delves into the technical nuances of both models, compa
 <script async src="https://cdn.jsdelivr.net/npm/chart.js"></script>
 <script defer src="../../javascript/benchmark.js"></script>
 
-<canvas id="modelComparisonChart" width="1024" height="400" active-models='["RTDETRv2", "PP-YOLOE+"]'></canvas>
+<canvas id="modelComparisonChart" width="1024" height="400" active-models='&#91;"RTDETRv2", "PP-YOLOE+"&#93;'></canvas>
 
 ## Model Overviews