Update README.md

README.md

@@ -17,13 +17,16 @@ 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
-and trained on [VideoFeedback](https://huggingface.co/datasets/TIGER-Lab/VideoFeedback),
-a large video evaluation dataset with multi-aspect human scores. 
+- 🧐🧐[VideoScore-anno-only](https://huggingface.co/TIGER-Lab/VideoScore-anno-only) is a variant from [VideoScore](https://huggingface.co/TIGER-Lab/VideoScore), trained on VideoFeedback dataset 
+excluding the real videos. 
 
-- VideoScore can reach 75+ Spearman correlation with humans on VideoEval-test, surpassing all the MLLM-prompting methods and feature-based metrics. 
+- [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.
 
-- VideoScore also beat the best baselines on other three benchmarks EvalCrafter, GenAI-Bench and VBench, showing high alignment with human evaluations.
+- 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.
+For the data details of four benchmarks, please refer to [VideoScore-Bench](https://huggingface.co/datasets/TIGER-Lab/VideoScore-Bench).
 
 - **This is the regression version of VideoScore**