Add pipeline tag and links to paper, project page, and code

This PR adds the `pipeline_tag: robotics` metadata to improve discoverability on the Hugging Face Hub, and adds links to the paper, project website, and GitHub repository in the model card body.

README.md

@@ -3,11 +3,16 @@ tags:
 - reinforcement-learning
 - robotics
 - dexterous-manipulation
+pipeline_tag: robotics
 ---
 
 # DexPolicy representative checkpoints
 
-This repository contains a representative subset of the object-specific policies reported in the DexPolicy paper. The released pairs use the YCB mustard-bottle relocation task and isolate the paper's exploration-scheduling intervention under PPO, GRPO, and FPO.
+This repository contains a representative subset of the object-specific policies reported in the paper [DexPolicy: Scheduled Exploration for Trajectory-Guided Dexterous Manipulation](https://huggingface.co/papers/2610.00360).  
+Project page: [https://aigeeksgroup.github.io/DexPolicy/](https://aigeeksgroup.github.io/DexPolicy/)  
+Code: [https://github.com/AIGeeksGroup/DexPolicy](https://github.com/AIGeeksGroup/DexPolicy)
+
+The released pairs use the YCB mustard-bottle relocation task and isolate the paper's exploration-scheduling intervention under PPO, GRPO, and FPO.
 
 ## Checkpoints
 
@@ -24,4 +29,4 @@ The PPO and FPO pairs train for approximately 5M environment steps with matched
 
 The PPO and GRPO `.zip` archives follow the Stable-Baselines3 checkpoint layout and include the policy, PyTorch variables, optimizer state, and library-version metadata. The FPO `.pt` files are PyTorch training checkpoints for the conditional-flow actor and critic. These policies are object-specific and are not presented as a single cross-object policy.
 
-This is a compact representative release rather than the complete multi-object checkpoint suite.
+This is a compact representative release rather than the complete multi-object checkpoint suite.