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README.md

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+---
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
+
+This repository contains the model weights for GDSD, as presented in the paper [GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models](https://arxiv.org/abs/2605.29398).
+
+Guided Denoiser Self-Distillation (GDSD) is a reinforcement learning (RL) framework tailored for diffusion large language models (dLLMs). It improves performance by directly distilling the denoiser from an advantage-guided self-teacher, bypassing the biases typically found in evidence lower bound (ELBO) based likelihood surrogates.
+
+## Links
+
+- **Paper:** [arXiv:2605.29398](https://arxiv.org/abs/2605.29398)
+- **GitHub Repository:** [https://github.com/GaryBall/GDSD](https://github.com/GaryBall/GDSD)
+
+## Citation
+
+If you find this work helpful, please consider citing:
+
+```bibtex
+@misc{tang2026gdsdreinforcementlearningguided,
+      title={GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models}, 
+      author={Xiaohang Tang and Keyue Jiang and Che Liu and Qifang Zhao and Xiaoxiao Xu and Sangwoong Yoon and Ilija Bogunovic},
+      year={2026},
+      eprint={2605.29398},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2605.29398}, 
+}
+```