Update README.md

README.md

@@ -12,6 +12,11 @@ library_name: transformers
 
 [Project Page](https://rlhf-v.github.io/) | [GitHub ](https://github.com/RLHF-V/RLHF-V) | [Demo](http://120.92.209.146:8081/) | [Paper](https://arxiv.org/abs/2312.00849) 
 
+## News
+* [2024.05.20] 🎉 We introduce [RLAIF-V](https://github.com/RLHF-V/RLAIF-V), our new alignment framework that utilize open-source models for feedback generation and reach **super GPT-4V trustworthiness**. You can download the corresponding [🤗 dataset](https://huggingface.co/datasets/openbmb/RLAIF-V-Dataset) now! 
+* [2024.04.11] 🔥 Our data is used in [MiniCPM-V 2.0](https://huggingface.co/openbmb/MiniCPM-V-2), an **end-side** multimodal large language model that exhibits **comparable trustworthiness with GPT-4V**!
+
+## Brief Introduction
 RLHF-V is an open-source multimodal large language model with the **lowest hallucination rate** on both long-form instructions and short-form questions. 
 
 RLHF-V is trained on [RLHF-V-Dataset](https://huggingface.co/datasets/HaoyeZhang/RLHF-V-Dataset), which contains **fine-grained segment-level human corrections** on diverse instructions. The base model is trained on [UniMM-Chat](https://huggingface.co/datasets/Yirany/UniMM-Chat), which is a high-quality knowledge-intensive SFT dataset. We introduce a new method **Dense Direct Preference Optimization (DDPO)** that can make better use of the fine-grained annotations. 
@@ -20,10 +25,6 @@ For more details, please refer to our [paper](https://arxiv.org/abs/2312.00849).
 
 ![Illustration of the RLHF-V framework](https://rlhf-v.github.io/images/rlhf-v_framework.jpg)
 
-## News
-* [2024.05.20] 🎉 We introduce [RLAIF-V](https://github.com/RLHF-V/RLAIF-V), our new alignment framework that utilize open-source models for feedback generation and reach **super GPT-4V trustworthiness**. You can download the corresponding [🤗 dataset](https://huggingface.co/datasets/openbmb/RLAIF-V-Dataset) now! 
-* [2024.04.11] 🔥 Our data is used in [MiniCPM-V 2.0](https://huggingface.co/openbmb/MiniCPM-V-2), an **end-side** multimodal large language model that exhibits **comparable trustworthiness with GPT-4V**!
-
 ## Model Details
 
 ### Model Description