Improve model card with pipeline tag and library name

This PR improves the model card by:

- Adding the `pipeline_tag: image-text-to-text`, ensuring the model is easily discoverable when searching for image-to-text models.
- Specifying the `library_name: transformers`, which enables the "How to use this model" widget on the model page.
- Correcting the arXiv link in the README.

README.md

@@ -1,21 +1,22 @@
 ---
 license: apache-2.0
+pipeline_tag: image-text-to-text
+library_name: transformers
 ---
 
-
 <p align="center">
   <img src="https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/q3Anm7o-MoNYjB8JztGVT.png" width="60%" />
 </p>
 
 <font size=3><div align='center' >  
-[[📖 arXiv Paper](https://arxiv.org/abs/2502.10391)] 
+[[📖 arXiv Paper](https://arxiv.org/abs/2505.02835)] 
 [[📊 R1-Reward Code](https://github.com/yfzhang114/r1_reward)] 
 [[📝 R1-Reward Data](https://huggingface.co/datasets/yifanzhang114/R1-Reward-RL)] 
 </div></font>
 
 # Training Multimodal Reward Model Through Stable Reinforcement Learning
 
-🔥 We are proud to open-source **R1-Reward**, a comprehensive project for improve reward modeling through reinforcement learning. This release includes:
+🔥 We are proud to open-source **R1-Reward**, a comprehensive project for improving reward modeling through reinforcement learning. This release includes:
 
 *   **R1-Reward Model:** A state-of-the-art (SOTA) multimodal reward model demonstrating substantial gains (Voting@15):
     *   **13.5%** improvement on VL Reward-Bench.
@@ -45,5 +46,4 @@ If you find it useful for your research and applications, please cite related pa
 - [MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?](https://github.com/yfzhang114/MME-RealWorld)
 - [MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs](https://arxiv.org/abs/2411.15296)
 - [Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models](https://github.com/yfzhang114/SliME)
-- [VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction](https://github.com/VITA-MLLM/VITA)
-
+- [VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction](https://github.com/VITA-MLLM/VITA)