diff --git a/docs/userguide/enflame-device/enable-enflame-gcu-sharing.md b/docs/userguide/enflame-device/enable-enflame-gcu-sharing.md
index 687050dc..bad5e7ba 100644
--- a/docs/userguide/enflame-device/enable-enflame-gcu-sharing.md
+++ b/docs/userguide/enflame-device/enable-enflame-gcu-sharing.md
@@ -7,13 +7,13 @@ title: Enable Enflame GPU Sharing
 
 **HAMi now supports sharing on enflame.com/gcu(i.e., S60) by implementing most device-sharing features as nvidia-GPU**, including:
 
-***GCU sharing***: Each task can allocate a portion of GCU instead of a whole GCU card, thus GCU can be shared among multiple tasks.
+**GCU sharing**: Each task can allocate a portion of GCU instead of a whole GCU card, thus GCU can be shared among multiple tasks.
 
-***Device Memory and Core Control***: GCUs can be allocated with certain percentage of device memory and core, we make sure that it does not exceed the boundary.
+**Device Memory and Core Control**: GCUs can be allocated with a certain percentage of device memory and core, with hard limits enforced to prevent exceeding the allocation.
 
-***Device UUID Selection***: You can specify which GCU devices to use or exclude using annotations.
+**Device UUID Selection**: You can specify which GCU devices to use or exclude using annotations.
 
-***Very Easy to use***: You don't need to modify your task yaml to use our scheduler. All your GPU jobs will be automatically supported after installation.
+**No task YAML changes required**: All GCU jobs are automatically supported after installation.
 
 ## Prerequisites
 
diff --git a/docs/userguide/iluvatar-device/enable-iluvatar-gpu-sharing.md b/docs/userguide/iluvatar-device/enable-iluvatar-gpu-sharing.md
index 3f4e5761..0b9c22ab 100644
--- a/docs/userguide/iluvatar-device/enable-iluvatar-gpu-sharing.md
+++ b/docs/userguide/iluvatar-device/enable-iluvatar-gpu-sharing.md
@@ -6,15 +6,15 @@ title: Enable Iluvatar GPU Sharing
 
 **HAMi now supports iluvatar.ai/gpu(i.e., MR-V100, BI-V150, BI-V100) by implementing most device-sharing features as nvidia-GPU**, including:
 
-***GPU sharing***: Each task can allocate a portion of GPU instead of a whole GPU card, thus GPU can be shared among multiple tasks.
+**GPU sharing**: Each task can allocate a portion of GPU instead of a whole GPU card, thus GPU can be shared among multiple tasks.
 
-***Device Memory Control***: GPUs can be allocated with a specific device memory size, with hard limits enforced to prevent exceeding the allocation.
+**Device Memory Control**: GPUs can be allocated with a specific device memory size, with hard limits enforced to prevent exceeding the allocation.
 
-***Device Core Control***: GPUs can be allocated with limited compute cores, with hard limits enforced to prevent exceeding the allocation.
+**Device Core Control**: GPUs can be allocated with limited compute cores, with hard limits enforced to prevent exceeding the allocation.
 
-***Device UUID Selection***: You can specify which GPU devices to use or exclude using annotations.
+**Device UUID Selection**: You can specify which GPU devices to use or exclude using annotations.
 
-***Very Easy to use***: You don't need to modify your task yaml to use our scheduler. All your GPU jobs will be automatically supported after installation.
+**No task YAML changes required**: All GPU jobs are automatically supported after installation.
 
 ## Prerequisites