Strict growth of ReLU expressivity with every hidden layer

Prove or disprove that, for every integer $\ell\leq\lceil\log_2(d+1)\rceil$, the inclusion $ReLU_d(\ell-1)\subsetneq ReLU_d(\ell)$ is strict, equivalently determining whether successive hidden layers strictly increase the class of exactly representable CPWL functions up to logarithmic depth.

Background

Here ReLUd()ReLU_d(\ell) denotes the set of CPWL functions on Rd computable with \ell hidden ReLU layers. The conjecture would establish that the logarithmic-depth upper bound is tight layer by layer, rather than merely showing that some function requires a particular depth.

The paper states that this conjecture has been confirmed only in special cases and remains unresolved in general. It further identifies the maximum function as a key candidate for separating consecutive depth classes, but the general conjecture is not settled.

References

Formally, if $ReLU_d(\ell)$ denotes the set of CPWL functions on $Rd$ that can be computed with $\ell$ hidden layers, the conjecture is that $ReLU_d(\ell-1) \subsetneq ReLU_d(\ell)$ for all $\ell \leq \lceil \log_2(d + 1) \rceil$.

Depth-Bounds for Neural Networks via the Braid Arrangement  (2502.09324 - Grillo et al., 13 Feb 2025) in Section 1, Introduction; Conjecture 2