diff --git a/README.md b/README.md
index 9fae275..a9c7dbd 100644
--- a/README.md
+++ b/README.md
@@ -66,13 +66,14 @@ kdtree_seq = KDTree(data; parallel=false)
 A kNN search finds the `k` nearest neighbors to a given point or points. This is done with the methods:
 
 ```julia
-knn(tree, point[s], k [, skip=always_false]) -> idxs, dists
-knn!(idxs, dists, tree, point, k [, skip=always_false])
+knn(tree, point[s], k [, sortres=false, skip=always_false]) -> idxs, dists
+knn!(idxs, dists, tree, point, k [, sortres=false, skip=always_false])
 ```
 
 * `tree`: The tree instance.
 * `point[s]`: A vector or matrix of points to find the `k` nearest neighbors for. A vector of numbers represents a single point; a matrix means the `k` nearest neighbors for each point (column) will be computed. `points` can also be a vector of vectors.
 * `k`: Number of nearest neighbors to find.
+* `sortres`: Whether to sort the returned values by their `distances` (`true`) or not (default: `false`).
 * `skip` (optional): A predicate function to skip certain points, e.g., points already visited.
 
 
diff --git a/src/knn.jl b/src/knn.jl
index 7e13659..2d1905e 100644
--- a/src/knn.jl
+++ b/src/knn.jl
@@ -5,7 +5,7 @@ function check_k(tree, k)
 end
 
 """
-    knn(tree::NNTree, points, k [, skip=always_false]) -> indices, distances
+    knn(tree::NNTree, points, k [, sortres=false, skip=always_false]) -> indices, distances
 
 Performs a lookup of the `k` nearest neighbors to the `points` from the data
 in the `tree`.
@@ -14,6 +14,7 @@ in the `tree`.
 - `tree`: The tree instance
 - `points`: Query point(s) - can be a vector (single point), matrix (multiple points), or vector of vectors
 - `k`: Number of nearest neighbors to find
+- `sortres`: Whether to sort the returned values by their `distances` (`true`) or not (default: `false`)
 - `skip`: Optional predicate function to skip points based on their index (default: `always_false`)
 
 # Returns
@@ -53,7 +54,7 @@ function knn_point!(tree::NNTree{V}, point::AbstractVector{T}, sortres, dist, id
 end
 
 """
-    knn!(idxs, dists, tree, point, k [, skip=always_false])
+    knn!(idxs, dists, tree, point, k [, sortres=false, skip=always_false])
 
 Same functionality as `knn` but stores the results in the input vectors `idxs` and `dists`.
 Useful to avoid allocations or specify the element type of the output vectors.
@@ -64,6 +65,7 @@ Useful to avoid allocations or specify the element type of the output vectors.
 - `tree`: The tree instance
 - `point`: Query point
 - `k`: Number of nearest neighbors to find
+- `sortres`: Whether to sort the returned values by their `distances` (`true`) or not (default: `false`)
 - `skip`: Optional predicate function to skip points based on their index (default: `always_false`)
 
 See also: `knn`, `nn`.