Add model card for GDSD (#1)

- Add model card for GDSD (c3d984ec86a63206bf2061755f07adefe3bdd350)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -0,0 +1,29 @@
+---
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# 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://huggingface.co/papers/2605.29398).
+
+Guided Denoiser Self-Distillation (GDSD) is a reinforcement learning framework for diffusion language models (dLLMs). It improves the denoiser of dLLMs by distilling from an advantage-guided self-teacher, bypassing the biases associated with evidence lower bound (ELBO) surrogates used in prior methods. GDSD provides a more stable and effective RL procedure, achieving significant performance gains on planning, math, and coding benchmarks.
+
+## Resources
+
+- **Paper:** [GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models](https://arxiv.org/abs/2605.29398)
+- **GitHub Repository:** [https://github.com/GaryBall/GDSD](https://github.com/GaryBall/GDSD)
+
+## Citation
+
+```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}, 
+}
+```