Update README.md

README.md

@@ -17,9 +17,13 @@ pipeline_tag: visual-question-answering
 ![VideoScore](https://tiger-ai-lab.github.io/VideoScore/static/images/teaser.png)
 
 ## Introduction
-- VideoScore is a video quality evaluation model, taking [Mantis-8B-Idefics2](https://huggingface.co/TIGER-Lab/Mantis-8B-Idefics2) as base-model
+
+- 🤯🤯Try on the new version [VideoScore-v1.1](https://huggingface.co/TIGER-Lab/VideoScore-v1.1), which is a variant from [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore) with better performance in "text-to-video alignment" subscore!
+See more details about this new version [here](https://huggingface.co/TIGER-Lab/VideoScore-v1.1).
+
+- [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore) series is a video quality evaluation model series, taking [Mantis-8B-Idefics2](https://huggingface.co/TIGER-Lab/Mantis-8B-Idefics2) as base-model
 and trained on [VideoFeedback](https://huggingface.co/datasets/TIGER-Lab/VideoFeedback),
-a large video evaluation dataset with multi-aspect human scores. 
+a large video evaluation dataset with multi-aspect human scores.
 
 - VideoScore can reach 75+ Spearman correlation with humans on VideoFeedback-test, surpassing all the MLLM-prompting methods and feature-based metrics.
 VideoScore also beat the best baselines on other three benchmarks EvalCrafter, GenAI-Bench and VBench, showing high alignment with human evaluations.