Method ambiguities with SparseArrays.jl

MWE:

using ReverseDiff
function f2(x)
    xv = @view x[1:end-1]
    xend = x[end]
    x = [xv; xend]
    return sum(x)
end
ReverseDiff.gradient(f2, rand(10)) # works

using SparseArrays
ReverseDiff.gradient(f2, rand(10)) # fails
#=
ERROR: MethodError: vcat(::SubArray{…}, ::ReverseDiff.TrackedReal{…}) is ambiguous.

Candidates:
  vcat(var"389"::AbstractVector, x::ReverseDiff.TrackedReal)
    @ ReverseDiff ~/.julia/packages/ReverseDiff/rKZaG/src/derivatives/arrays.jl:41
  vcat(X1::Union{Number, AbstractVecOrMat{<:Number}}, X::Union{Number, AbstractVecOrMat{<:Number}}...)
    @ SparseArrays ~/.julia/juliaup/julia-1.12.2+0.aarch64.apple.darwin14/share/julia/stdlib/v1.12/SparseArrays/src/sparsevector.jl:1275

Possible fix, define
  vcat(::AbstractVector{<:Number}, ::ReverseDiff.TrackedReal)
=#

The issues caused by the SparseArrays.jl definitions of hcat/vcat are I think well known (https://github.com/JuliaSparse/SparseArrays.jl/issues/431) but what I'm seeing from is that the solution for now is to define the necessary methods in ReverseDiff (?).

I think just adding :(AbstractVector{<:Number}) (and :(AbstractMatrix{<:Number})) to this line should fix it?

https://github.com/JuliaDiff/ReverseDiff.jl/blob/7cc65886962c82973e5d3877d8d05c3722063dd9/src/derivatives/arrays.jl#L36

Start by reproducing the ambiguity with the MWE in the issue, then inspect the hcat/vcat derivative definitions around src/derivatives/arrays.jl:36. Confirm the relevant method signatures and check that the gradient call completes without a MethodError; the issue is done when this SparseArrays combination dispatches unambiguously.