Update README.md

README.md

@@ -13,14 +13,14 @@ size_categories:
 
 # TimeLens-Bench
 
-📑 [**Paper**](TODO) | 💻 [**Code**](https://github.com/TencentARC/TimeLens) | 🏠 [**Project Page**](https://timelens-arc-lab.github.io/) | 🤗 [**Model & Data**](https://huggingface.co/collections/TencentARC/TimeLens)
+📑 [**Paper**](TODO) | 💻 [**Code**](https://github.com/TencentARC/TimeLens) | 🏠 [**Project Page**](https://timelens-arc-lab.github.io/) | 🤗 [**Model & Data**](https://huggingface.co/collections/TencentARC/TimeLens) | 🏆 [**TimeLens-Bench Leaderboard**](https://timelens-arc-lab.github.io/#leaderboard)
 
 ## ✨ Dataset Description
 
 **TimeLens-Bench** is a comprehensive, high-quality evaluation benchmark for video temporal grounding, proposed in our paper [TimeLens: Rethinking Video Temporal Grounding with Multimodal LLMs](TODO).
 
-During our annotation process, we identified critical quality issues within existing datasets and performed extensive manual corrections. We observed a **dramatic re-ranking of models** on TimeLens-Bench compared to legacy benchmarks, demonstrating that TimeLens-Bench provides *more reliable* evaluation
-(more details in our [paper](TODO) and [project page](https://timelens-arc-lab.github.io/)).
+During our annotation process, we identified critical quality issues within existing datasets and performed extensive manual corrections. We observed a **dramatic re-ranking of models** on TimeLens-Bench compared to legacy benchmarks, demonstrating that TimeLens-Bench provides **more reliable evaluation** for video temporal grounding.
+(See more details in our [paper](TODO) and [project page](https://timelens-arc-lab.github.io/).)
 <img src="https://cdn-uploads.huggingface.co/production/uploads/65372e922c6ef949b22c26d9/31s82GO6S5LKlW0-kcIFU.png" alt="performance_comparison_charades-1" width="35%">
 
 ### Dataset Statistics