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README.md

@@ -25,7 +25,7 @@ _An [ACT (Action Chunking Transformer)](https://tonyzhaozh.github.io/aloha/) pol
 
 **🔗 项目仓库 / Project repos**：
 - [vitorcen/isaaclab-experience](https://github.com/vitorcen/isaaclab-experience) — Isaac Lab + LeIsaac 多策略横评（parent project）
-- [vitorcen/LeIsaac](https://github.com/vitorcen/LeIsaac) — LeIsaac fork（训练脚本 + 设计文档 / training scripts + design docs）
+- [vitorcen/LeIsaac-Training](https://github.com/vitorcen/LeIsaac-Training) — LeIsaac fork（训练脚本 + 设计文档 / training scripts + design docs）
 
 ## TL;DR
 
@@ -66,8 +66,8 @@ _Training recipe_
 | Wall-clock | ~5 hours |
 | Recipe credit | [shadowHokage/act_policy](https://huggingface.co/shadowHokage/act_policy) |
 
-训练入口脚本在我们的 LeIsaac fork：[`scripts/training/act/train.sh`](https://github.com/vitorcen/LeIsaac/blob/main/scripts/training/act/train.sh)。
-_Training entrypoint script lives in our LeIsaac fork: [`scripts/training/act/train.sh`](https://github.com/vitorcen/LeIsaac/blob/main/scripts/training/act/train.sh)._
+训练入口脚本在我们的 LeIsaac fork：[`scripts/training/act/train.sh`](https://github.com/vitorcen/LeIsaac-Training/blob/main/scripts/training/act/train.sh)。
+_Training entrypoint script lives in our LeIsaac fork: [`scripts/training/act/train.sh`](https://github.com/vitorcen/LeIsaac-Training/blob/main/scripts/training/act/train.sh)._
 
 ## 评测结果
 _Eval results_
@@ -122,7 +122,7 @@ python -m lerobot.async_inference.policy_server --host 0.0.0.0 --port 8080
 
 ### 2. 客户端启动 LeIsaac eval
 
-通过我们的 [vitorcen/LeIsaac](https://github.com/vitorcen/LeIsaac) fork：
+通过我们的 [vitorcen/LeIsaac-Training](https://github.com/vitorcen/LeIsaac-Training) fork：
 
 ```bash
 cd LeIsaac
@@ -158,7 +158,7 @@ _Related_
   - [`wsagi/DiffusionPolicy-PickOrange`](https://huggingface.co/wsagi/DiffusionPolicy-PickOrange) — 自训 Diffusion Policy (267M, DDIM 32-step swap)
   - [`shadowHokage/act_policy`](https://huggingface.co/shadowHokage/act_policy) — 同配方公开 ckpt（我们的复刻参考）
   - [`LightwheelAI/leisaac-pick-orange-v0`](https://huggingface.co/LightwheelAI/leisaac-pick-orange-v0) — GR00T N1.5 SOTA（30s 完成 3 颗）
-- 完整训练 + eval 配方：[vitorcen/LeIsaac](https://github.com/vitorcen/LeIsaac) fork
+- 完整训练 + eval 配方：[vitorcen/LeIsaac-Training](https://github.com/vitorcen/LeIsaac-Training) fork
 
 ## 致谢
 _Acknowledgments_