Given an $n$-vertex bipartite graph $I=(S,U,E)$, the goal of set cover problem is to find a minimum sized subset of $S$ such that every vertex in $U$ is adjacent to some vertex of this subset. It is NP-hard to approximate set cover to within a $(1-o(1))\ln n$ factor. If we use the size of the optimum solution $k$ as the parameter, then it can be solved in $n^{k+o(1)}$ time. A natural question is: can we approximate set cover to within an $o(\ln n)$ factor in $n^{k-\epsilon}$ time? In a recent breakthrough result, Karthik, Laekhanukit and Manurangsi showed that assuming the Strong Exponential Time Hypothesis (SETH), for any computable function $f$, no $f(k)\cdot n^{k-\epsilon}$-time algorithm can approximate set cover to a factor below $(\log n)^{\frac{1}{poly(k,e(\epsilon))}}$ for some function $e$. This paper presents a simple gap-producing reduction which, given a set cover instance $I=(S,U,E)$ and two integers $k

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