diff --git a/base/abstractarray.jl b/base/abstractarray.jl
index af29aee6a74b6..239e75df52510 100644
--- a/base/abstractarray.jl
+++ b/base/abstractarray.jl
@@ -1716,13 +1716,7 @@ end
 _cs(d, a, b) = (a == b ? a : throw(DimensionMismatch(
     "mismatch in dimension $d (expected $a got $b)")))
 
-function dims2cat(::Val{dims}) where dims
-    if any(≤(0), dims)
-        throw(ArgumentError("All cat dimensions must be positive integers, but got $dims"))
-    end
-    ntuple(in(dims), maximum(dims))
-end
-
+dims2cat(::Val{dims}) where dims = dims2cat(dims)
 function dims2cat(dims)
     if any(≤(0), dims)
         throw(ArgumentError("All cat dimensions must be positive integers, but got $dims"))
@@ -1730,9 +1724,8 @@ function dims2cat(dims)
     ntuple(in(dims), maximum(dims))
 end
 
-_cat(dims, X...) = cat_t(promote_eltypeof(X...), X...; dims=dims)
+_cat(dims, X...) = _cat_t(dims, promote_eltypeof(X...), X...)
 
-@inline cat_t(::Type{T}, X...; dims) where {T} = _cat_t(dims, T, X...)
 @inline function _cat_t(dims, ::Type{T}, X...) where {T}
     catdims = dims2cat(dims)
     shape = cat_size_shape(catdims, X...)
@@ -1742,6 +1735,9 @@ _cat(dims, X...) = cat_t(promote_eltypeof(X...), X...; dims=dims)
     end
     return __cat(A, shape, catdims, X...)
 end
+# this version of `cat_t` is not very kind for inference and so its usage should be avoided,
+# nevertheless it is here just for compat after https://github.com/JuliaLang/julia/pull/45028
+@inline cat_t(::Type{T}, X...; dims) where {T} = _cat_t(dims, T, X...)
 
 # Why isn't this called `__cat!`?
 __cat(A, shape, catdims, X...) = __cat_offset!(A, shape, catdims, ntuple(zero, length(shape)), X...)
@@ -1880,8 +1876,8 @@ julia> reduce(hcat, vs)
 """
 hcat(X...) = cat(X...; dims=Val(2))
 
-typed_vcat(::Type{T}, X...) where T = cat_t(T, X...; dims=Val(1))
-typed_hcat(::Type{T}, X...) where T = cat_t(T, X...; dims=Val(2))
+typed_vcat(::Type{T}, X...) where T = _cat_t(Val(1), T, X...)
+typed_hcat(::Type{T}, X...) where T = _cat_t(Val(2), T, X...)
 
 """
     cat(A...; dims)
@@ -1917,7 +1913,8 @@ julia> cat(true, trues(2,2), trues(4)', dims=(1,2))
 ```
 """
 @inline cat(A...; dims) = _cat(dims, A...)
-_cat(catdims, A::AbstractArray{T}...) where {T} = cat_t(T, A...; dims=catdims)
+# `@constprop :aggressive` allows `catdims` to be propagated as constant improving return type inference
+@constprop :aggressive _cat(catdims, A::AbstractArray{T}...) where {T} = _cat_t(catdims, T, A...)
 
 # The specializations for 1 and 2 inputs are important
 # especially when running with --inline=no, see #11158
@@ -1928,12 +1925,12 @@ hcat(A::AbstractArray) = cat(A; dims=Val(2))
 hcat(A::AbstractArray, B::AbstractArray) = cat(A, B; dims=Val(2))
 hcat(A::AbstractArray...) = cat(A...; dims=Val(2))
 
-typed_vcat(T::Type, A::AbstractArray) = cat_t(T, A; dims=Val(1))
-typed_vcat(T::Type, A::AbstractArray, B::AbstractArray) = cat_t(T, A, B; dims=Val(1))
-typed_vcat(T::Type, A::AbstractArray...) = cat_t(T, A...; dims=Val(1))
-typed_hcat(T::Type, A::AbstractArray) = cat_t(T, A; dims=Val(2))
-typed_hcat(T::Type, A::AbstractArray, B::AbstractArray) = cat_t(T, A, B; dims=Val(2))
-typed_hcat(T::Type, A::AbstractArray...) = cat_t(T, A...; dims=Val(2))
+typed_vcat(T::Type, A::AbstractArray) = _cat_t(Val(1), T, A)
+typed_vcat(T::Type, A::AbstractArray, B::AbstractArray) = _cat_t(Val(1), T, A, B)
+typed_vcat(T::Type, A::AbstractArray...) = _cat_t(Val(1), T, A...)
+typed_hcat(T::Type, A::AbstractArray) = _cat_t(Val(2), T, A)
+typed_hcat(T::Type, A::AbstractArray, B::AbstractArray) = _cat_t(Val(2), T, A, B)
+typed_hcat(T::Type, A::AbstractArray...) = _cat_t(Val(2), T, A...)
 
 # 2d horizontal and vertical concatenation
 
diff --git a/stdlib/LinearAlgebra/src/special.jl b/stdlib/LinearAlgebra/src/special.jl
index 8d4292c6045ed..098df785e557a 100644
--- a/stdlib/LinearAlgebra/src/special.jl
+++ b/stdlib/LinearAlgebra/src/special.jl
@@ -414,14 +414,14 @@ const _TypedDenseConcatGroup{T} = Union{Vector{T}, Adjoint{T,Vector{T}}, Transpo
 
 promote_to_array_type(::Tuple{Vararg{Union{_DenseConcatGroup,UniformScaling}}}) = Matrix
 
-Base._cat(dims, xs::_DenseConcatGroup...) = Base.cat_t(promote_eltype(xs...), xs...; dims=dims)
+Base._cat(dims, xs::_DenseConcatGroup...) = Base._cat_t(dims, promote_eltype(xs...), xs...)
 vcat(A::Vector...) = Base.typed_vcat(promote_eltype(A...), A...)
 vcat(A::_DenseConcatGroup...) = Base.typed_vcat(promote_eltype(A...), A...)
 hcat(A::Vector...) = Base.typed_hcat(promote_eltype(A...), A...)
 hcat(A::_DenseConcatGroup...) = Base.typed_hcat(promote_eltype(A...), A...)
 hvcat(rows::Tuple{Vararg{Int}}, xs::_DenseConcatGroup...) = Base.typed_hvcat(promote_eltype(xs...), rows, xs...)
 # For performance, specially handle the case where the matrices/vectors have homogeneous eltype
-Base._cat(dims, xs::_TypedDenseConcatGroup{T}...) where {T} = Base.cat_t(T, xs...; dims=dims)
+Base._cat(dims, xs::_TypedDenseConcatGroup{T}...) where {T} = Base._cat_t(dims, T, xs...)
 vcat(A::_TypedDenseConcatGroup{T}...) where {T} = Base.typed_vcat(T, A...)
 hcat(A::_TypedDenseConcatGroup{T}...) where {T} = Base.typed_hcat(T, A...)
 hvcat(rows::Tuple{Vararg{Int}}, xs::_TypedDenseConcatGroup{T}...) where {T} = Base.typed_hvcat(T, rows, xs...)
diff --git a/test/abstractarray.jl b/test/abstractarray.jl
index d650cf67ebf11..df2dbe1c198b9 100644
--- a/test/abstractarray.jl
+++ b/test/abstractarray.jl
@@ -733,6 +733,10 @@ function test_cat(::Type{TestAbstractArray})
     cat3v(As) = cat(As...; dims=Val(3))
     @test @inferred(cat3v(As)) == zeros(2, 2, 2)
     @test @inferred(cat(As...; dims=Val((1,2)))) == zeros(4, 4)
+
+    r = rand(Float32, 56, 56, 64, 1);
+    f(r) = cat(r, r, dims=(3,))
+    @inferred f(r);
 end
 
 function test_ind2sub(::Type{TestAbstractArray})
diff --git a/test/ambiguous.jl b/test/ambiguous.jl
index e7b3b13fba0ff..8d8c3efab53b9 100644
--- a/test/ambiguous.jl
+++ b/test/ambiguous.jl
@@ -172,20 +172,11 @@ using LinearAlgebra, SparseArrays, SuiteSparse
 # not using isempty so this prints more information when it fails
 @testset "detect_ambiguities" begin
     let ambig = Set{Any}(((m1.sig, m2.sig) for (m1, m2) in detect_ambiguities(Core, Base; recursive=true, ambiguous_bottom=false, allowed_undefineds)))
-        @test isempty(ambig)
-        expect = []
         good = true
-        while !isempty(ambig)
-            sigs = pop!(ambig)
-            i = findfirst(==(sigs), expect)
-            if i === nothing
-                println(stderr, "push!(expect, (", sigs[1], ", ", sigs[2], "))")
-                good = false
-                continue
-            end
-            deleteat!(expect, i)
+        for (sig1, sig2) in ambig
+            @test sig1 === sig2 # print this ambiguity
+            good = false
         end
-        @test isempty(expect)
         @test good
     end