Update README.md

README.md

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-<a href='https://arxiv.org/abs/'><img src='https://img.shields.io/badge/arXiv-paper-red'></a><a href='https://ruili33.github.io/tpo_website.github.io/'><img src='https://img.shields.io/badge/project-TPO-blue'></a><a href='https://huggingface.co/collections/ruili0/temporal-preference-optimization-67874b451f65db189fa35e10'><img src='https://img.shields.io/badge/huggingface-datasets-green'></a>
+<a href='https://arxiv.org/abs/'><img src='https://img.shields.io/badge/arXiv-paper-red'></a><a href='https://ruili33.github.io/tpo_website.github.io/'><img src='https://img.shields.io/badge/project-TPO-blue'></a>
 <a href='https://huggingface.co/collections/ruili0/temporal-preference-optimization-67874b451f65db189fa35e10'><img src='https://img.shields.io/badge/model-checkpoints-yellow'></a> 
 <a href='https://github.com/ruili33/TPO'><img src='https://img.shields.io/badge/github-repository-purple'></a> 
 <img src="cvpr_figure_TPO.png"></img>
 # LLaVA-Video-7B-Qwen2-TPO
 
 LLaVA-Video-7B-Qwen2-TPO, introduced by paper [Temporal Preference Optimization for Long-form Video Understanding](https://arxiv.org/abs), optimized
-by temporal preference based on LLaVA-Video-7B-Qwen2. LLaVA-Video-7B-Qwen2-TPO achieves state-of-the-art performance on a variety of benchmarks,
-achieving the strongest 7B model on the Video-MME benchmark.
+by temporal preference based on LLaVA-Video-7B-Qwen2. The LLaVA-Video-7B-Qwen2-TPO model establishes state-of-the-art performance across a range of 
+benchmarks, demonstrating an average performance improvement of 1.5% compared to LLaVA-Video-7B. 
+Notably, it emerges as the leading 7B parameter model on the Video-MME benchmark.