Update README.md

README.md

@@ -12,10 +12,10 @@ This repository contains the official model weights and code for the paper: **"R
 - 🌐 [Project Page](https://rti-dp.github.io/)
 - 💻 [Code](https://github.com/RTI-DP/rti-dp)
 
-Diffusion Policies have demonstrated impressive performance in robotic manipulation tasks. However, their long inference time, stemming from extensive iterative denoising, limits their applicability to latency-critical tasks. Inspired by the Real-Time Iteration (RTI) Scheme from optimal control, RTI-DP introduces a novel approach to significantly reduce inference time without the need for additional training or policy redesign. This scheme accelerates optimization by leveraging solutions from previous time steps as initial guesses, enabling seamless integration into many pre-trained diffusion-based models and making them suitable for real-time robotic applications with comparable performance.
+RTI-DP enables fast inference in diffusion-based robotic policies by initializing each denoising step with the previous prediction — no retraining, no distillation.
 
 <div align="center">
-  <img src="https://github.com/RTI-DP/rti-dp/raw/main/media/rti-dp.gif" alt="RTI-DP Teaser" width="600"/>
+  <img src="https://rti-dp.github.io/static/images/rti.png" alt="RTI-DP Teaser" width="600"/>
 </div>
 
 ## Usage
@@ -37,10 +37,14 @@ For RTI-DP-scale checkpoints, refer to the [duandaxia/rti-dp-scale](https://hugg
 If you find our work useful, please consider citing our paper:
 
 ```bibtex
-@misc{duan2025rtidp,
-    title={Real-Time Iteration Scheme for Diffusion Policy},
-    author={Yufei Duan and Hang Yin and Danica Kragic},
-    year={2025},
+@misc{duan2025realtimeiterationschemediffusion,
+      title={Real-Time Iteration Scheme for Diffusion Policy}, 
+      author={Yufei Duan and Hang Yin and Danica Kragic},
+      year={2025},
+      eprint={2508.05396},
+      archivePrefix={arXiv},
+      primaryClass={cs.RO},
+      url={https://arxiv.org/abs/2508.05396}, 
 }
 ```