Let $A_n$ be a random $n \times n$ matrix with entries in $\{-1, +1\}$. As usual, "random" here means with respect to the uniform measure over such matrices.
The strong version of the singularity conjecture is that, as $n \to \infty$, $$ \mathbb{P}\{ \text{det}(A_n) = 0\} = (1 +o(1)) \, n^2 2^{-(n-1)} $$ I understand the right hand side comes from the fact that there are $2 \binom{n}{2} \sim n^2 $ possible selections of rows and columns and that $2^{-(n-1)}$ is the probability that any such pair is equal up to sign.
However, this is not a rigorous argument, since it ignores the dependence of such selections of rows and columns. Is there a rigorous lower bound that matches the asymptotics above that handles the dependence issues?