diff --git a/v2.5.x/site/en/userGuide/schema/sparse_vector.md b/v2.5.x/site/en/userGuide/schema/sparse_vector.md
index e0062c03c..746c0eb69 100644
--- a/v2.5.x/site/en/userGuide/schema/sparse_vector.md
+++ b/v2.5.x/site/en/userGuide/schema/sparse_vector.md
@@ -563,17 +563,21 @@ For more information on similarity search parameters, refer to [​Basic ANN Sea
 
 When using sparse vectors in Milvus, consider the following limits:
 
-- Currently, only the __IP__ distance metric is supported for sparse vectors.
+- Currently, only the __IP__ distance metric is supported for sparse vectors. The high dimensionality of sparse vectors makes L2 and cosine distance impractical.
 
 - For sparse vector fields, only the __SPARSE_INVERTED_INDEX__ and __SPARSE_WAND__ index types are supported.
 
-- Currently, [range search](range-search.md), [grouping search](grouping-search.md), and [search iterator](with-iterators.md) are not supported for sparse vectors.
+- The data types supported for sparse vectors:
 
-## FAQ
+    - The dimension part must be an unsigned 32-bit integer;
+    - The value part can be a non-negative 32-bit floating-point number.
+
+- Sparse vectors must meet the following requirements for insertion and search:
 
-- __What distance metric is supported for sparse vectors?__
+    - At least one value in the vector is non-zero;
+    - Vector indices are non-negative.
 
-    Sparse vectors only support the Inner Product (IP) distance metric due to the high dimensionality of sparse vectors, which makes L2 distance and cosine distance impractical.
+## FAQ
 
 - __Can you explain the difference between SPARSE_INVERTED_INDEX and SPARSE_WAND, and how do I choose between them?__
 
@@ -583,10 +587,6 @@ When using sparse vectors in Milvus, consider the following limits:
 
     The choice of __drop_ratio_build__ and __drop_ratio_search__ depends on the characteristics of your data and your requirements for search latency/throughput and accuracy.
 
-- __What data types are supported for sparse embeddings?__
-
-    The dimension part must be an unsigned 32-bit integer, and the value part can be a non-negative 32-bit floating-point number.
-
 - __Can the dimension of a sparse embedding be any discrete value within the uint32 space?__
 
     Yes, with one exception. The dimension of a sparse embedding can be any value in the range of `[0, maximum of uint32)`. This means you cannot use the maximum value of uint32.
@@ -598,8 +598,3 @@ When using sparse vectors in Milvus, consider the following limits:
 - __Is it possible to have both sparse and dense vectors in a single collection?__
 
     Yes, with multiple vector type support, you can create collections with both sparse and dense vector columns and perform hybrid searches on them.
-
-- __What are the requirements for sparse embeddings to be inserted or searched?__
-
-    Sparse embeddings must have at least one non-zero value, and vector indices must be non-negative.
-
diff --git a/v2.5.x/yarn.lock b/v2.5.x/yarn.lock
index b2a0815da..a1453c8fa 100644
--- a/v2.5.x/yarn.lock
+++ b/v2.5.x/yarn.lock
@@ -4,21 +4,21 @@
 
 argparse@^1.0.10:
   version "1.0.10"
-  resolved "https://registry.npmjs.org/argparse/-/argparse-1.0.10.tgz"
+  resolved "https://registry.yarnpkg.com/argparse/-/argparse-1.0.10.tgz#bcd6791ea5ae09725e17e5ad988134cd40b3d911"
   integrity sha512-o5Roy6tNG4SL/FOkCAN6RzjiakZS25RLYFrcMttJqbdd8BWrnA+fGz57iN5Pb06pvBGvl5gQ0B48dJlslXvoTg==
   dependencies:
     sprintf-js "~1.0.2"
 
 autolinker@^3.11.0:
   version "3.16.2"
-  resolved "https://registry.npmjs.org/autolinker/-/autolinker-3.16.2.tgz"
+  resolved "https://registry.yarnpkg.com/autolinker/-/autolinker-3.16.2.tgz#6bb4f32432fc111b65659336863e653973bfbcc9"
   integrity sha512-JiYl7j2Z19F9NdTmirENSUUIIL/9MytEWtmzhfmsKPCp9E+G35Y0UNCMoM9tFigxT59qSc8Ml2dlZXOCVTYwuA==
   dependencies:
     tslib "^2.3.0"
 
 remarkable@^2.0.1:
   version "2.0.1"
-  resolved "https://registry.npmjs.org/remarkable/-/remarkable-2.0.1.tgz"
+  resolved "https://registry.yarnpkg.com/remarkable/-/remarkable-2.0.1.tgz#280ae6627384dfb13d98ee3995627ca550a12f31"
   integrity sha512-YJyMcOH5lrR+kZdmB0aJJ4+93bEojRZ1HGDn9Eagu6ibg7aVZhc3OWbbShRid+Q5eAfsEqWxpe+g5W5nYNfNiA==
   dependencies:
     argparse "^1.0.10"
@@ -26,10 +26,10 @@ remarkable@^2.0.1:
 
 sprintf-js@~1.0.2:
   version "1.0.3"
-  resolved "https://registry.npmjs.org/sprintf-js/-/sprintf-js-1.0.3.tgz"
+  resolved "https://registry.yarnpkg.com/sprintf-js/-/sprintf-js-1.0.3.tgz#04e6926f662895354f3dd015203633b857297e2c"
   integrity sha512-D9cPgkvLlV3t3IzL0D0YLvGA9Ahk4PcvVwUbN0dSGr1aP0Nrt4AEnTUbuGvquEC0mA64Gqt1fzirlRs5ibXx8g==
 
 tslib@^2.3.0:
   version "2.6.3"
-  resolved "https://registry.npmjs.org/tslib/-/tslib-2.6.3.tgz"
+  resolved "https://registry.yarnpkg.com/tslib/-/tslib-2.6.3.tgz#0438f810ad7a9edcde7a241c3d80db693c8cbfe0"
   integrity sha512-xNvxJEOUiWPGhUuUdQgAJPKOOJfGnIyKySOc09XkKsgdUV/3E2zvwZYdejjmRgPCgcym1juLH3226yA7sEFJKQ==