Improve model card: add metadata, paper link and repository information

Hi! I'm Niels from the Hugging Face community science team.

This PR improves the model card for the DRPG Judge Model by:
- Adding the `library_name: transformers` metadata (verified by the `config.json` architecture and version).
- Adding the `pipeline_tag: text-generation` for better discoverability.
- Linking the model to its associated paper on Hugging Face: [DRPG (Decompose, Retrieve, Plan, Generate): An Agentic Framework for Academic Rebuttal](https://huggingface.co/papers/2601.18081).
- Including a BibTeX citation for researchers using this model.

Please feel free to merge if this looks good!

README.md

@@ -1,5 +1,44 @@
 ---
 license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+base_model: qwen/Qwen3-8B
+tags:
+- academic-rebuttal
+- agentic-framework
+- rl
 ---
-A judge model to evaluate rebuttal quality, trained from Qwen3-8B using RL.
-Refer to https://github.com/ulab-uiuc/DRPG-RebuttalAgent for usage.
+
+# DRPG Judge Model
+
+This repository contains the Judge Model for the **DRPG (Decompose, Retrieve, Plan, Generate)** framework, as introduced in the paper [DRPG (Decompose, Retrieve, Plan, Generate): An Agentic Framework for Academic Rebuttal](https://huggingface.co/papers/2601.18081).
+
+The model is specifically designed to evaluate the quality of academic rebuttals. It was trained from **Qwen3-8B** using Reinforcement Learning (RL) to provide accurate and persuasive assessment scores.
+
+## Links
+- **Paper:** [DRPG: An Agentic Framework for Academic Rebuttal](https://huggingface.co/papers/2601.18081)
+- **Repository:** [ulab-uiuc/DRPG-RebuttalAgent](https://github.com/ulab-uiuc/DRPG-RebuttalAgent)
+
+## About DRPG
+DRPG is an agentic framework for automatic academic rebuttal generation that operates through four steps:
+1. **Decompose**: Breaking reviews into atomic concerns.
+2. **Retrieve**: Finding relevant evidence from the paper.
+3. **Plan**: Identifying feasible rebuttal strategies.
+4. **Generate**: Creating targeted responses.
+
+The Judge Model is used within this pipeline to assess rebuttal quality, achieving performance beyond the average human level in experimental evaluations.
+
+## Usage
+Refer to the official [GitHub repository](https://github.com/ulab-uiuc/DRPG-RebuttalAgent) for instructions on running the evaluation scripts and using the model within the DRPG pipeline.
+
+## Citation
+If you find this model useful in your research, please cite:
+```bibtex
+@article{han2025drpg,
+  title={DRPG (Decompose, Retrieve, Plan, Generate): An Agentic Framework for Academic Rebuttal},
+  author={Han, Peixuan and Yu, Yingjie and Xu, Jingjun and You, Jiaxuan},
+  journal={arXiv preprint arXiv:2601.18081},
+  url={https://arxiv.org/pdf/2601.18081},
+  year={2026}
+}
+```