diff --git a/site/en/faq/product_faq.md b/site/en/faq/product_faq.md
index cdcb9b8fc..d5b25f8f0 100644
--- a/site/en/faq/product_faq.md
+++ b/site/en/faq/product_faq.md
@@ -174,6 +174,10 @@ Milvus supports Binary, Float32, Float16, and BFloat16 vector types.
 - Float32 vectors: Default storage with a precision of about 7 decimal digits. Even Float64 values are stored with Float32 precision, leading to potential precision loss upon retrieval.
 - Float16 and BFloat16 vectors: Offer reduced precision and memory usage. Float16 is suitable for applications with limited bandwidth and storage, while BFloat16 balances range and efficiency, commonly used in deep learning to reduce computational requirements without significantly impacting accuracy.
 
+#### Does Milvus support specifying default values for scalar or vector fields?
+
+Currently, Milvus 2.4.x does not support specifying default values for scalar or vector fields. This feature is planned for future releases.
+
 #### Still have questions?
 
 You can:
diff --git a/site/en/getstarted/install-overview.md b/site/en/getstarted/install-overview.md
index c31b61688..3d9e5f828 100644
--- a/site/en/getstarted/install-overview.md
+++ b/site/en/getstarted/install-overview.md
@@ -44,6 +44,10 @@ The selection of a deployment mode typically depends on the development stage of
 
 The choice of Milvus deployment mode depends on your project's stage and scale. Milvus provides a flexible and powerful solution for various needs, from rapid prototyping to large-scale enterprise deployment.
 
+- **Milvus Lite** is recommended for smaller datasets, up to a few million vectors.
+- **Milvus Standalone** is suitable for medium-sized datasets, scaling up to 100 million vectors.
+- **Milvus Distributed** is designed for large-scale deployments, capable of handling datasets from 100 million up to tens of billions of vectors.
+
 ![Select deployment option for your use case](../../../assets/select-deployment-option.png)
 
 ## Comparison on functionalities
diff --git a/site/en/userGuide/manage-collections.md b/site/en/userGuide/manage-collections.md
index 2d0d68f35..6af8c27c2 100644
--- a/site/en/userGuide/manage-collections.md
+++ b/site/en/userGuide/manage-collections.md
@@ -335,11 +335,11 @@ export fields='[{ \
   <tbody>
     <tr>
       <td><code>auto_id</code></td>
-      <td>Whether allows the primary field to automatically increment.<br>Setting this to <strong>True</strong> makes the primary field automatically increment. In this case, the primary field should not be included in the data to insert to avoid errors.</td>
+      <td>Determines if the primary field automatically increments.<br>Setting this to <strong>True</strong> makes the primary field automatically increment. In this case, the primary field should not be included in the data to insert to avoid errors. The auto-generated IDs have a fixed length and cannot be altered.</td>
     </tr>
     <tr>
       <td><code>enable_dynamic_field</code></td>
-      <td>Whether allows Milvus saves the values of undefined fields in a dynamic field if the data being inserted into the target collection includes fields that are not defined in the collection's schema.<br>When you set this to <strong>True</strong>, Milvus will create a field called <strong>$meta</strong> to store any undefined fields and their values from the data that is inserted.</td>
+      <td>Determines if Milvus saves the values of undefined fields in a dynamic field if the data being inserted into the target collection includes fields that are not defined in the collection's schema.<br>When you set this to <strong>True</strong>, Milvus will create a field called <strong>$meta</strong> to store any undefined fields and their values from the data that is inserted.</td>
     </tr>
     <tr>
       <td><code>field_name</code></td>