Add missing metadata: library_name, license, and pipeline_tag

README.md

@@ -1,6 +1,9 @@
 ---
-{}
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
 ---
+
 <h1 align="center">
 <em>AReaL</em>: Ant Reasoning Reinforcement Learning for LLMs
 </h1>
@@ -37,7 +40,7 @@ In our AReaL-boba² (A-ReaL-double-boba) release, we highlight the top 3 most im
 
 + Experimental support for **multi-turn** agentic RL training. Check our [complete example](https://inclusionai.github.io/AReaL/customization/agent.html).
 
-For the complete system design and more training details, please check [our v0.3 blog](/blog/AReaL_v0_3.md) and our [research paper](about:blank) for a more comprehensive presentation of our system design.
+For the complete system design and more training details, please check [our v0.3 blog](/blog/AReaL_v0_3.md) and our [research paper](https://arxiv.org/pdf/2505.24298).
 
 ### Overview of Asynchronous RL Training
 
@@ -100,8 +103,6 @@ AReaL-boba² allows you to independently customize the [dataset](https://inclusi
 
 In particular, we show a simple example to develop a multi-turn math agent for RL training. Please see the learning curve below and reference the [step-by-step guide](https://inclusionai.github.io/AReaL/customization/agent.html) if you want to implement your own agentic RL project.
 
-**Multi-turn Agent Learning Curve**
-
 ## Getting Started
 
 ### Quick Start
@@ -214,4 +215,4 @@ We also appreciate all the pioneering works from the community, particularly the
       primaryClass={cs.LG},
       url={https://arxiv.org/abs/2505.24298}, 
 }
-```
+```