tldr -- Building general polynomials with QSVT requires implementing controlled versions of vanilla QSVT circuits. Is this a trivial task? Does it change the complexity? How is it done in practice?
Quantum singular value transformation (QSVT) allows applying polynomial transformations to singular values of some matrix $A$ block-encoded into a unitary matrix $U$. A typical QSVT circuit looks something like (ignoring some details) $$U_{\phi}=\prod_i \Pi(\phi_{2i})U^\dagger \Pi(\phi_{2i+1})U$$ and consists of applications of $U$ and $U^\dagger$ interleaved with projector-based rotations.
The result is that $U_{\phi}$ block-encodes some polynomial function of $A$. However, the range of polynomials obtained in this way is limited and not always practical. E.g. they need to have definite parities and could not directly implement $e^{-ixt}$.
A workaround for this is to build two block-embeddings $U^{even}_\phi$ and $U^{odd}_\phi$ and combine them via the linear combination of unitaries. To do this, we need to be able to implement controlled versions of $U^{even/odd}_\phi$ and in particular controlled versions of $U,U^\dagger$ as well as $\Pi(\phi)$.
Is it in general easy to implement controlled $U/\Pi(\phi)$ or is this an independent assumption? Does implementing $C(U_\phi)$ change the complexity of the QSVT?