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  license: mit
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  ---
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  <p align="center">
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  <img src="https://github.com/yinjjiew/Data/raw/main/dllm-rl/figure1.png" width="100%"/>
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  </p>
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  </p>
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- # Introduction to TraDo
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-
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- We introduce **TraDo**, SOTA diffusion language model, trained with **TraceRL**.
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-
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- * **TraDo-4B-Instruct** and **TraDo-8B-Instruct** outperform similarly sized strong AR models across math reasoning tasks.
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- * **TraDo-8B-Thinking** is the first Long-CoT diffusion language model.
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- [Paper](https://arxiv.org/abs/2506.03136) | [Code](https://github.com/Gen-Verse/dLLM-RL)
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  # Citation
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  ```
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- @article{wang2025cure,
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- title={Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning},
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- author={Wang, Yinjie and Yang, Ling and Tian, Ye and Shen, Ke and Wang, Mengdi},
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- journal={arXiv preprint arXiv:2506.03136},
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  year={2025}
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  }
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  ```
 
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  license: mit
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  ---
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+ # Introduction to TraDo
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+
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+ [Paper](https://arxiv.org/abs/2509.06949) | [Code](https://github.com/Gen-Verse/dLLM-RL)
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+
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+ We introduce **TraDo**, SOTA diffusion language model, trained with **TraceRL**.
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+
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+ * **TraDo-4B-Instruct** and **TraDo-8B-Instruct** outperform similarly sized strong AR models across math reasoning tasks.
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+ * **TraDo-8B-Thinking** is the first Long-CoT diffusion language model.
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+
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+
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+
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  <p align="center">
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  <img src="https://github.com/yinjjiew/Data/raw/main/dllm-rl/figure1.png" width="100%"/>
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  </p>
 
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  </p>
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  # Citation
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  ```
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+ @article{wang2025trado,
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+ title={Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models},
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+ author={Wang, Yinjie and Yang, Ling and Li, Bowen and Tian, Ye and Shen, Ke and Wang, Mengdi},
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+ journal={arXiv preprint arXiv:2509.06949},
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  year={2025}
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  }
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  ```