diff --git a/README.md b/README.md
index 7f4f6da..ed55e4c 100644
--- a/README.md
+++ b/README.md
@@ -38,7 +38,7 @@ TransferQueue offers **fine-grained, sub-sample-level** data management and **lo
  - **Dec 30, 2025**: **TransferQueue x verl** integration has been tested with the DAPO algorithm at scale **(64 nodes, 1024 cards)**. It significantly optimizes host memory utilization and accelerates data transfers. Stay tuned for more details!
  - **Dec 20, 2025**: 🔥 The official [tutorial](https://github.com/Ascend/TransferQueue/tree/main/tutorial) is released! Feel free to check it out.
  - **Nov 10, 2025**: We disentangled the data retrieval logic from TransferQueueController [PR#101](https://github.com/TransferQueue/TransferQueue/pull/101). Now you can implement your own `Sampler` to customize data consumption.
- - **Nov 5, 2025**: We provide a `KVStorageManager` that simplifies the integration with KV-based storage backends [PR#96](https://github.com/TransferQueue/TransferQueue/pull/96). The first available KV-based backend is [Yuanrong](https://gitcode.com/openeuler/yuanrong-datasystem).
+ - **Nov 5, 2025**: We provide a `KVStorageManager` that simplifies the integration with KV-based storage backends [PR#96](https://github.com/TransferQueue/TransferQueue/pull/96). The first available KV-based backend is [openYuanrong](https://gitcode.com/openeuler/yuanrong-datasystem).
  - **Nov 4, 2025**: Data partitioning capability is available in [PR#98](https://github.com/TransferQueue/TransferQueue/pull/98). Now you can define logical data partitions to manage your train/val/test datasets.
  - **Oct 25, 2025**: Storage backends are now pluggable in [PR#66](https://github.com/TransferQueue/TransferQueue/pull/66). You can try to integrate your own storage backend with TransferQueue now!
  - **Oct 21, 2025**: Early integration with verl is ready [verl/pull/3649](https://github.com/volcengine/verl/pull/3649). Following PRs will optimize the single controller architecture by fully decoupling data & control flows.
diff --git a/scripts/performance_test/draw_figure.py b/scripts/performance_test/draw_figure.py
index 400c7b9..2db0a0c 100644
--- a/scripts/performance_test/draw_figure.py
+++ b/scripts/performance_test/draw_figure.py
@@ -32,7 +32,7 @@
 # All normalization lives here so the shell script keeps simple lowercase names.
 BACKEND_DISPLAY_NAMES = {
     "simplestorage": "SimpleStorage",
-    "yuanrong": "Yuanrong",
+    "yuanrong": "openYuanrong",
     "mooncakestore": "MooncakeStore",
     "ray_baseline": "Ray",
 }
@@ -96,7 +96,7 @@ def make_xlabel(size_label: str) -> str:
 df["Scenario"] = df["backend_parsed"]
 
 # Set backend display order: only include backends that actually exist in the data
-preferred_backend_order = ["Ray", "SimpleStorage", "Yuanrong", "MooncakeStore"]
+preferred_backend_order = ["Ray", "SimpleStorage", "openYuanrong", "MooncakeStore"]
 
 # Get actual backends present in the data, maintaining preferred order
 actual_backends = df["Scenario"].unique().tolist()