Update Images

README.md

@@ -1,80 +1,80 @@
----
-base_model:
-- GSAI-ML/LLaDA-8B-Instruct
-pipeline_tag: text-generation
----
-# RemeDi: <u><b>Rem</b></u>asking-<u><b>e</b></u>nabled <u><b>Di</b></u>ffusion Language Model
-
-
-<div align="center">
-
-
-[![weixin](https://img.shields.io/badge/-WeChat@MAPLE实验室-000000?logo=wechat&logoColor=07C160)](https://mp.weixin.qq.com/s/UefnjlCSi6YvzVe-Xu9jjQ)
-[![RemeDi](https://img.shields.io/badge/Paper-RemeDi-2b9348.svg?logo=arXiv)](https://arxiv.org/abs/2509.23653)&#160;
-
-[![Static Badge](https://img.shields.io/badge/Model(9B)-yellow?logoColor=violet&label=%F0%9F%A4%97%20RemeDi-Instruct%20checkpoint)](https://huggingface.co/maple-research-lab/RemeDi-Instruct)&#160;
-[![Static Badge](https://img.shields.io/badge/Model(9B)-yellow?logoColor=violet&label=%F0%9F%A4%97%20RemeDi-RL%20checkpoints)](https://huggingface.co/maple-research-lab/RemeDi-RL)&#160;
-
-</div>
-
-# 🔬 Method Overview
-
-RemeDi lets every token be revised at every diffusion step. Instead of fixing in an early guess, the model evaluates the quality of each token and can remask low-confidence positions, allowing later steps to resample them with richer context—built-in self-correction.
-
-RemeDi extends the original model with a dual-stream transformer:
-
-- Token Prediction Stream (TPS) predicts masked tokens as usual.
-
-- Unmasking Policy Stream (UPS) outputs per-token confidence scores, deciding which tokens to unmask or remask.
-
-
-At each denoising step, tokens with low confidence can be remasked and resampled, enabling iterative refinement.
-For the training and RL algorithms, see the Methods section of the paper.
-
-<p align="center">
-  <!-- Replace with the actual image path -->
-  <img src="figures/figure1.png" alt="RemeDi architecture and performance radar" width="600">
-</p>
-
-
-
-# 📈 Key Results
-
-
-<p align="center">
-  <!-- Replace with the actual image path -->
-  <img src="figures/figure2.png" alt="RemeDi performance table" width="600">
-</p>
-
-
-
-# 📂 Repository Structure
-
-```
-├── inference.py     # inference scripts
-├── remedi/          # networks configs 
-└── README.md
-```
-
-# 🚀 Inference
-
-To run inference, execute: 
-
-```sh
-git clone https://github.com/maple-research-lab/RemeDi.git
-cd RemeDi
-
-# chat with remedi
-python inference.py
-```
-
-# 📥 Citation
-
-```
-@article{huang2025don,
-  title={Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models},
-  author={Huang, Zemin and Wang, Yuhang and Chen, Zhiyang and Qi, Guo-Jun},
-  journal={arXiv preprint arXiv:2509.23653},
-  year={2025}
-}
-```
+---
+base_model:
+- GSAI-ML/LLaDA-8B-Instruct
+pipeline_tag: text-generation
+---
+# RemeDi: <u><b>Rem</b></u>asking-<u><b>e</b></u>nabled <u><b>Di</b></u>ffusion Language Model
+
+
+<div align="center">
+
+
+[![weixin](https://img.shields.io/badge/-WeChat@MAPLE实验室-000000?logo=wechat&logoColor=07C160)](https://mp.weixin.qq.com/s/UefnjlCSi6YvzVe-Xu9jjQ)
+[![RemeDi](https://img.shields.io/badge/Paper-RemeDi-2b9348.svg?logo=arXiv)](https://arxiv.org/abs/2509.23653)&#160;
+
+[![Static Badge](https://img.shields.io/badge/Model(9B)-yellow?logoColor=violet&label=%F0%9F%A4%97%20RemeDi-Instruct%20checkpoint)](https://huggingface.co/maple-research-lab/RemeDi-Instruct)&#160;
+[![Static Badge](https://img.shields.io/badge/Model(9B)-yellow?logoColor=violet&label=%F0%9F%A4%97%20RemeDi-RL%20checkpoints)](https://huggingface.co/maple-research-lab/RemeDi-RL)&#160;
+
+</div>
+
+# 🔬 Method Overview
+
+RemeDi lets every token be revised at every diffusion step. Instead of fixing in an early guess, the model evaluates the quality of each token and can remask low-confidence positions, allowing later steps to resample them with richer context—built-in self-correction.
+
+RemeDi extends the original model with a dual-stream transformer:
+
+- Token Prediction Stream (TPS) predicts masked tokens as usual.
+
+- Unmasking Policy Stream (UPS) outputs per-token confidence scores, deciding which tokens to unmask or remask.
+
+
+At each denoising step, tokens with low confidence can be remasked and resampled, enabling iterative refinement.
+For the training and RL algorithms, see the Methods section of the paper.
+
+<p align="center">
+  <!-- Replace with the actual image path -->
+  <img src="https://github.com/maple-research-lab/RemeDi/blob/main/figures/figure1.png?raw=true" alt="RemeDi architecture and performance radar" width="600">
+</p>
+
+
+
+# 📈 Key Results
+
+
+<p align="center">
+  <!-- Replace with the actual image path -->
+  <img src="https://github.com/maple-research-lab/RemeDi/blob/main/figures/figure2.png?raw=true" alt="RemeDi performance table" width="600">
+</p>
+
+
+
+# 📂 Repository Structure
+
+```
+├── inference.py     # inference scripts
+├── remedi/          # networks configs 
+└── README.md
+```
+
+# 🚀 Inference
+
+To run inference, execute: 
+
+```sh
+git clone https://github.com/maple-research-lab/RemeDi.git
+cd RemeDi
+
+# chat with remedi
+python inference.py
+```
+
+# 📥 Citation
+
+```
+@article{huang2025don,
+  title={Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models},
+  author={Huang, Zemin and Wang, Yuhang and Chen, Zhiyang and Qi, Guo-Jun},
+  journal={arXiv preprint arXiv:2509.23653},
+  year={2025}
+}
+```