A bounded-independence variant of the Berry-Esseen theorem
There are variants of Berry-Esseen for bounded independence, although I have not seen one which is as general as the original theorem. For example Theorem 5.1. in Diakonikolas, Kane, Nelson implies a Berry-Esseen theorem for weighted sums of Bernoulli random variables with bounded independence, as long as none of the weights is too large. If you want error $\varepsilon$ (i.e. Kolmogorov distance from the Gaussian distribution), then $\Theta(1/\varepsilon^2)$-wise independence is necessary and sufficient.