  We study the behaviour of a symmetric exclusion process in the presence of
non-Markovian stochastic resetting, where the configuration of the system is
reset to a step-like profile at power-law waiting times with an exponent
$\alpha$. We find that the power-law resetting leads to a rich behaviour for
the currents, as well as density profile. We show that, for any finite system,
for $\alpha<1$, the density profile eventually becomes uniform while for
$\alpha >1$, an eventual non-trivial stationary profile is reached. We also
find that, in the limit of thermodynamic system size, at late times, the
average diffusive current grows $\sim t^\theta$ with $\theta = 1/2$ for $\alpha
\le 1/2$, $\theta = \alpha$ for $1/2 < \alpha \le 1$ and $\theta=1$ for $\alpha
> 1$. We also analytically characterize the distribution of the diffusive
current in the short-time regime using a trajectory-based perturbative
approach. Using numerical simulations, we show that in the long-time regime,
the diffusive current distribution follows a scaling form with an
$\alpha-$dependent scaling function. We also characterise the behaviour of the
total current using renewal approach. We find that the average total current
also grows algebraically $\sim t^{\phi}$ where $\phi = 1/2$ for $\alpha \le 1$,
$\phi=3/2-\alpha$ for $1 < \alpha \le 3/2$, while for $\alpha > 3/2$ the
average total current reaches a stationary value, which we compute exactly. The
variance of the total current also shows an algebraic growth with an exponent
$\Delta=1$ for $\alpha \le 1$, and $\Delta=2-\alpha$ for $1 < \alpha \le 2$,
whereas it approaches a constant value for $\alpha>2$. The total current
distribution remains non-stationary for $\alpha<1$, while, for $\alpha>1$, it
reaches a non-trivial and strongly non-Gaussian stationary distribution, which
we also compute using the renewal approach.
