diff --git a/Project.toml b/Project.toml
index f630477..e8dfb17 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "RecursiveFactorization"
 uuid = "f2c3362d-daeb-58d1-803e-2bc74f2840b4"
 authors = ["Yingbo Ma <mayingbo5@gmail.com>"]
-version = "0.2.21"
+version = "0.2.22"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
diff --git a/src/lu.jl b/src/lu.jl
index ed462dd..458ab4d 100644
--- a/src/lu.jl
+++ b/src/lu.jl
@@ -1,7 +1,7 @@
 using LoopVectorization
 using TriangularSolve: ldiv!
 using LinearAlgebra: BlasInt, BlasFloat, LU, UnitLowerTriangular, checknonsingular, BLAS,
-    LinearAlgebra, Adjoint, Transpose, UpperTriangular, AbstractVecOrMat
+                     LinearAlgebra, Adjoint, Transpose, UpperTriangular, AbstractVecOrMat
 using StrideArraysCore
 using Polyester: @batch
 
@@ -41,32 +41,35 @@ init_pivot(::Val{true}, minmn) = Vector{BlasInt}(undef, minmn)
 
 if CUSTOMIZABLE_PIVOT && isdefined(LinearAlgebra, :_ipiv_cols!)
     function LinearAlgebra._ipiv_cols!(::LU{<:Any, <:Any, NotIPIV}, ::OrdinalRange,
-        B::StridedVecOrMat)
+            B::StridedVecOrMat)
         return B
     end
 end
 if CUSTOMIZABLE_PIVOT && isdefined(LinearAlgebra, :_ipiv_rows!)
     function LinearAlgebra._ipiv_rows!(::(LU{T, <:AbstractMatrix{T}, NotIPIV} where {T}),
-        ::OrdinalRange,
-        B::StridedVecOrMat)
+            ::OrdinalRange,
+            B::StridedVecOrMat)
         return B
     end
 end
 if CUSTOMIZABLE_PIVOT
     function LinearAlgebra.ldiv!(A::LU{T, <:StridedMatrix, <:NotIPIV},
-        B::StridedVecOrMat{T}) where {T <: BlasFloat}
+            B::StridedVecOrMat{T}) where {T <: BlasFloat}
         ldiv!(UpperTriangular(A.factors), ldiv!(UnitLowerTriangular(A.factors), B))
     end
 end
 
-function lu!(A, pivot = Val(true), thread = Val(false); check = true, kwargs...)
+function lu!(A, pivot = Val(true), thread = Val(false);
+        check::Union{Bool, Val{true}, Val{false}} = Val(true), kwargs...)
     m, n = size(A)
     minmn = min(m, n)
     npivot = normalize_pivot(pivot)
     # we want the type on both branches to match. When pivot = Val(false), we construct
     # a `NotIPIV`, which `LinearAlgebra.generic_lufact!` does not.
     F = if pivot === Val(true) && minmn < 10 # avx introduces small performance degradation
-        LinearAlgebra.generic_lufact!(A, to_stdlib_pivot(pivot); check = check)
+        LinearAlgebra.generic_lufact!(A, to_stdlib_pivot(pivot);
+            check = ((check isa Bool && check) || (check === Val(true)))
+        )
     else
         lu!(A, init_pivot(npivot, minmn), npivot, thread; check = check,
             kwargs...)
@@ -87,11 +90,11 @@ recurse(_) = false
 _ptrarray(ipiv) = PtrArray(ipiv)
 _ptrarray(ipiv::NotIPIV) = ipiv
 function lu!(A::AbstractMatrix{T}, ipiv::AbstractVector{<:Integer},
-    pivot = Val(true), thread = Val(false);
-    check::Bool = true,
-    # the performance is not sensitive wrt blocksize, and 8 is a good default
-    blocksize::Integer = length(A) ≥ 40_000 ? 8 : 16,
-    threshold::Integer = pick_threshold()) where {T}
+        pivot = Val(true), thread = Val(false);
+        check::Union{Bool, Val{true}, Val{false}} = Val(true),
+        # the performance is not sensitive wrt blocksize, and 8 is a good default
+        blocksize::Integer = length(A) ≥ 40_000 ? 8 : 16,
+        threshold::Integer = pick_threshold()) where {T}
     pivot = normalize_pivot(pivot)
     info = zero(BlasInt)
     m, n = size(A)
@@ -113,12 +116,12 @@ function lu!(A::AbstractMatrix{T}, ipiv::AbstractVector{<:Integer},
     else # generic fallback
         info = _generic_lufact!(A, pivot, ipiv, info)
     end
-    check && checknonsingular(info)
+    ((check isa Bool && check) || (check === Val(true))) && checknonsingular(info)
     LU(A, ipiv, info)
 end
 
 @inline function recurse!(A, ::Val{Pivot}, m, n, mnmin, ipiv, info, blocksize,
-    ::Val{true}) where {Pivot}
+        ::Val{true}) where {Pivot}
     if length(A) * _sizeof(eltype(A)) >
        0.92 * LoopVectorization.VectorizationBase.cache_size(Val(2))
         _recurse!(A, Val{Pivot}(), m, n, mnmin, ipiv, info, blocksize, Val(true))
@@ -127,11 +130,11 @@ end
     end
 end
 @inline function recurse!(A, ::Val{Pivot}, m, n, mnmin, ipiv, info, blocksize,
-    ::Val{false}) where {Pivot}
+        ::Val{false}) where {Pivot}
     _recurse!(A, Val{Pivot}(), m, n, mnmin, ipiv, info, blocksize, Val(false))
 end
 @inline function _recurse!(A, ::Val{Pivot}, m, n, mnmin, ipiv, info, blocksize,
-    ::Val{Thread}) where {Pivot, Thread}
+        ::Val{Thread}) where {Pivot, Thread}
     info = reckernel!(A, Val(Pivot), m, mnmin, ipiv, info, blocksize, Val(Thread))::Int
     @inbounds if m < n # fat matrix
         # [AL AR]
@@ -175,7 +178,7 @@ Base.@propagate_inbounds function apply_permutation!(P, A, ::Val{false})
     nothing
 end
 function reckernel!(A::AbstractMatrix{T}, pivot::Val{Pivot}, m, n, ipiv, info, blocksize,
-    thread)::BlasInt where {T, Pivot}
+        thread)::BlasInt where {T, Pivot}
     @inbounds begin
         if n <= max(blocksize, 1)
             info = _generic_lufact!(A, Val(Pivot), ipiv, info)