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README.md

@@ -14,20 +14,23 @@ library_name: ltx-video
 ---
 
 <p align="center">
-  <img src="assets/image.png" alt="Echo-LongVideo generated video gallery" width="100%">
+  <img src="assets/image.png" alt="JoyAI-Echo generated video gallery" width="100%">
 </p>
 
 <div align="center">
 
-<h1>Echo-LongVideo</h1>
+<h1>JoyAI-Echo</h1>
 
 <p><strong>🎬 Pushing the Frontier of Long Video Generation</strong></p>
 
 <p>Official model weights for <strong>minute-level multi-shot audio-video generation</strong> with a distilled DMD generator, paired cross-modal memory, and story-level consistency.</p>
 
+<p><strong>For academic research and non-commercial use only.</strong></p>
+
 <p>
-  <a href="LongVideo_Tech_Report.pdf"><b>📄 Paper</b></a> |
-  <a href="https://github.com/Echo-Team-Joy-Future-Academy-JD/JoyAI-Echo"><b>💻 Inference Code</b></a> |
+  <a href="https://github.com/jd-opensource/JoyAI-Echo/blob/main/joyai-echo%20tech%20report.pdf"><b>📄 Paper</b></a> |
+  <a href="https://echo-team-joy-future-academy-jd.github.io/Echo-LongVideo-Page/"><b>🌐 Project Page</b></a> |
+  <a href="https://github.com/jd-opensource/JoyAI-Echo"><b>💻 Inference Code</b></a> |
   <a href="#model-details"><b>🧬 Model</b></a> |
   <a href="#usage"><b>🚀 Usage</b></a> |
   <a href="#results"><b>📊 Results</b></a> |
@@ -45,9 +48,9 @@ library_name: ltx-video
 
 ## Model Summary
 
-**Echo-LongVideo** (a.k.a. **JoyAI-Echo**) is a long-form, multi-shot, audio-video generation model. A cross-modal audio-visual memory bank preserves character appearance and voice timbre consistently across up to **five-minute** videos, and a post-training pipeline combining memory-based reinforcement learning with distribution matching distillation (DMD) delivers a **7.5× inference speedup** without sacrificing quality.
+**JoyAI-Echo** is a long-form, multi-shot, audio-video generation framework that breaks the barriers of error accumulation, weak temporal coherence, and prohibitive latency in long video generation. A cross-modal audio-visual memory bank preserves character appearance and voice timbre consistently over **five-minute** videos, while a post-training pipeline combining memory-based reinforcement learning with distribution matching distillation (DMD) delivers a **7.5× inference speedup** without sacrificing quality.
 
-In human evaluation, Echo-LongVideo decisively outperforms *HappyOyster* (directing mode) on long-form generation and surpasses the short-video specialist *Wan 2.6* on human-centric tasks.
+JoyAI-Echo decisively outperforms *HappyOyster* (directing mode) on long-form generation and even surpasses the short-video specialist *Wan 2.6* on human-centric tasks.
 
 This repository hosts the **released checkpoint**. Inference code is released separately — see the [Usage](#usage) section.
 
@@ -64,19 +67,23 @@ This repository hosts the **released checkpoint**. Inference code is released se
 
 ## Highlights
 
-- 🎞️ **Minute-level multi-shot stories** from a single prompt JSON.
-- ⚡ **DMD-distilled few-step inference**, ~7.5× faster than the original pipeline.
-- 🔊 **Joint audio-video generation** in a single pipeline.
-- 🧠 **Paired cross-modal memory bank** for story-level identity and voice consistency.
+- 🎞️ **Minute-level multi-shot stories**: generate a sequence of coherent shots from one prompt JSON.
+- ⚡ **DMD-distilled few-step inference**: ~7.5× faster than the original pipeline.
+- 🔊 **Joint audio-video generation**: one pipeline produces synchronized video and audio.
+- 🧠 **Paired cross-modal memory bank**: conditions each new shot on prior visual identity and voice context for story-level consistency.
+
+## Demo Gallery
+
+Explore long-form and short-form JoyAI-Echo cases on the [Project Page](https://echo-team-joy-future-academy-jd.github.io/Echo-LongVideo-Page/). 🍿
 
 ## Usage
 
-Inference is run with the standalone **Echo-LongVideo** inference repository.
+Inference is run with the standalone **JoyAI-Echo** inference repository.
 
 ### 1. Download the checkpoint
 
 ```bash
-huggingface-cli download <org>/Echo-LongVideo \
+huggingface-cli download jdopensource/JoyAI-Echo \
   --local-dir checkpoints
 ```
 
@@ -98,7 +105,7 @@ checkpoints/
 ### 2. Get the inference code
 
 ```bash
-git clone https://github.com/Echo-Team-Joy-Future-Academy-JD/JoyAI-Echo.git
+git clone https://github.com/jd-opensource/JoyAI-Echo.git
 cd JoyAI-Echo
 ```
 
@@ -119,10 +126,7 @@ Inside each string, write these parts in order:
 | **Style** | The overall visual and emotional aesthetic — e.g. realistic motorsport film language, cool daylight, restrained cinematic tension. |
 | **Camera Movement** | The shot type and framing or movement — e.g. a stable close-up on the face, or a medium shot from the waist up. |
 | **Background** | The setting and scene details behind the subject. |
-| **Sound Effects & BGM** | The sounds in the scene and the background music — e.g. room tone, wind, footsteps and fabric, with a soft low music bed under the dialogue or nobackground music |
-
-A more convenient prompt-writing workflow will be released as a **director agent** for everyone to use.
-
+| **Sound Effects & BGM** | The sounds in the scene and the background music — e.g. room tone, wind, footsteps and fabric, with a soft low music bed under the dialogue or no background music. |
 
 ### 4. Run
 
@@ -147,14 +151,14 @@ python inference.py --num-frames 121 --video-height 480 --video-width 832
 | Item | Value |
 | --- | ---: |
 | 🎬 Long-form coherent story length | **5 min** |
-| ⚡ Speedup over the original multi-step pipeline | **7.5×** |
+| ⚡ Generation speedup over the original multi-step pipeline | **7.5×** |
 | 📚 Benchmark stories | **100** |
 | 🎞️ Generated evaluation shots | **3,000** |
 | 🕒 Frames per shot | **241 @ 25 fps** |
 
 ### Human Evaluation
 
-GSB user study. Values are the percentage of user preferences.
+GSB user study on long- and short-video generation. The numbers denote the percentage of user preferences.
 
 | Aspect (Long Video) | JoyAI-Echo | Tie | HappyOyster (Directing) |
 | --- | ---: | ---: | ---: |
@@ -169,25 +173,36 @@ GSB user study. Values are the percentage of user preferences.
 | Audio quality | 32.3% | 30.9% | 36.8% |
 | Prompt following | 33.8% | 36.8% | 29.4% |
 
+## Links
+
+- Project page: [`https://echo-team-joy-future-academy-jd.github.io/Echo-LongVideo-Page/`](https://echo-team-joy-future-academy-jd.github.io/Echo-LongVideo-Page/)
+- Inference code: [`https://github.com/jd-opensource/JoyAI-Echo`](https://github.com/jd-opensource/JoyAI-Echo)
+- HuggingFace: [`https://huggingface.co/jdopensource/JoyAI-Echo`](https://huggingface.co/jdopensource/JoyAI-Echo)
+
 ## Acknowledgements
 
-We gratefully acknowledge [LTX-Video](https://github.com/Lightricks/LTX-Video) for the base video generator and [Gemma](https://huggingface.co/google/gemma-3-12b-it) for the text encoder, along with the broader open-source community.
+We gratefully acknowledge the open-source projects this work builds upon — in particular [LTX2.3](https://huggingface.co/Lightricks/LTX-2.3) for the base video generator and [Gemma](https://huggingface.co/google/gemma-3-12b-it) for the text encoder. Thanks to the broader research community whose contributions made this release possible.
 
 ## Citation
 
-If Echo-LongVideo helps your research or products, please cite:
+If JoyAI-Echo helps your research or products, please cite:
 
 ```bibtex
 @techreport{echo2026longvideo,
-  title        = {Echo-LongVideo: Pushing the Frontier of Long Video Generation},
+  title        = {JoyAI-Echo: Pushing the Frontier of Long Video Generation},
   author       = {{Echo Team @ Joy Future Academy, JD}},
   institution  = {Joy Future Academy, JD},
   year         = {2026},
-  month        = {June},
-  url          = {https://github.com/Echo-Team-Joy-Future-Academy-JD/JoyAI-Echo}
+  month        = {May}
 }
 ```
 
 ## License
 
-Released under the [LTX-2 Community License Agreement](https://github.com/Lightricks/LTX-2/blob/main/LICENSE). By downloading or using these weights, you agree to its terms. The bundled Gemma text encoder is governed by Google's separate Gemma license.
+This project is based on LTX-2 by Lightricks Ltd.
+
+Portions of the original LTX-2 codebase have been modified by JD.com for academic and research purposes only.
+This project is not intended for commercial use. For commercial use of LTX-2 or its derivatives, please contact Lightricks Ltd.
+
+All original copyright, license, patent, trademark, and attribution notices from LTX-2 are retained.
+This project remains subject to the LTX-2 Community License Agreement.