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

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