diff --git a/monai/losses/dice.py b/monai/losses/dice.py
index d8db2bf586..3094b7a747 100644
--- a/monai/losses/dice.py
+++ b/monai/losses/dice.py
@@ -613,11 +613,13 @@ def __init__(
 
             include_background: if False channel index 0 (background category) is excluded from the calculation.
             to_onehot_y: whether to convert `y` into the one-hot format. Defaults to False.
-            sigmoid: if True, apply a sigmoid function to the prediction.
-            softmax: if True, apply a softmax function to the prediction.
+            sigmoid: if True, apply a sigmoid function to the prediction, only used by the `DiceLoss`,
+                don't need to specify activation function for `CrossEntropyLoss`.
+            softmax: if True, apply a softmax function to the prediction, only used by the `DiceLoss`,
+                don't need to specify activation function for `CrossEntropyLoss`.
             other_act: if don't want to use `sigmoid` or `softmax`, use other callable function to execute
-                other activation layers, Defaults to ``None``. for example:
-                `other_act = torch.tanh`.
+                other activation layers, Defaults to ``None``. for example: `other_act = torch.tanh`.
+                only used by the `DiceLoss`, don't need to specify activation function for `CrossEntropyLoss`.
             squared_pred: use squared versions of targets and predictions in the denominator or not.
             jaccard: compute Jaccard Index (soft IoU) instead of dice or not.
             reduction: {``"mean"``, ``"sum"``}
@@ -727,11 +729,13 @@ def __init__(
             and other parameters are only used for dice loss.
             include_background: if False channel index 0 (background category) is excluded from the calculation.
             to_onehot_y: whether to convert `y` into the one-hot format. Defaults to False.
-            sigmoid: if True, apply a sigmoid function to the prediction.
-            softmax: if True, apply a softmax function to the prediction.
+            sigmoid: if True, apply a sigmoid function to the prediction, only used by the `DiceLoss`,
+                don't need to specify activation function for `FocalLoss`.
+            softmax: if True, apply a softmax function to the prediction, only used by the `DiceLoss`,
+                don't need to specify activation function for `FocalLoss`.
             other_act: if don't want to use `sigmoid` or `softmax`, use other callable function to execute
-                other activation layers, Defaults to ``None``. for example:
-                `other_act = torch.tanh`.
+                other activation layers, Defaults to ``None``. for example: `other_act = torch.tanh`.
+                only used by the `DiceLoss`, don't need to specify activation function for `FocalLoss`.
             squared_pred: use squared versions of targets and predictions in the denominator or not.
             jaccard: compute Jaccard Index (soft IoU) instead of dice or not.
             reduction: {``"none"``, ``"mean"``, ``"sum"``}