This paper studies the *refuter* problems, a family of decision-tree $\mathsf{TFNP}$ problems capturing the metamathematical difficulty of proving proof complexity lower bounds. Suppose $\varphi$ is a hard tautology that does not admit any length-$s$ proof in some proof system $P$. In the corresponding refuter problem, we are given (query access to) a purported length-$s$ proof $\pi$ in $P$ that claims to have proved $\varphi$, and our goal is to find an invalid derivation inside $\pi$. As suggested by witnessing theorems in bounded arithmetic, the *computational complexity* of these refuter problems is closely tied to the *metamathematics* of the underlying proof complexity lower bounds. We focus on refuter problems corresponding to lower bounds for *resolution*, which is arguably the single most studied system in proof complexity. We introduce a new class $\mathrm{rwPHP}(\mathsf{PLS})$ in decision-tree $\mathsf{TFNP}$, which can be seen as a randomized version of $\mathsf{PLS}$, and argue that this class effectively captures the metamathematics of proving resolution lower bounds. We view these results as a contribution to the *bounded reverse mathematics* of complexity lower bounds: when interpreted in relativized bounded arithmetic, our results show that the theory $\mathsf{T}^1_2(\alpha) + \mathrm{dwPHP}(\mathsf{PV}(\alpha))$ characterizes the "reasoning power" required to prove (the "easiest") resolution lower bounds. An intriguing corollary of our results is that the combinatorial principle, "the pigeonhole principle requires exponential-size resolution proofs", captures the class of $\mathsf{TFNP}$ problems whose totality is provable in $\mathsf{T}^1_2 + \mathrm{dwPHP}(\mathsf{PV})$.
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