Skimming the paper [1], the key difference they used is that their hash table insertion algorithm will probe further than the first empty slot, instead of greedily filling the first empty slot it finds. They combine this with a clever probing sequence which provably finds empty slots efficiently, even if the table is very full.

This means insertions when the hash table is less full are slower, but you avoid the worst-case scenario where you're probing for the last (few) remaining open slot(s) without any idea as to where they are.

[1]: https://arxiv.org/pdf/2501.02305

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An interesting theoretical result but I would expect the current 'trick' of simply allocating a larger table than necessary to be the superior solution in practice. For example, Rust's hashbrown intentionally leaves 1/8th (12.5%) of the table empty, which does cost a bit more memory but makes insertions/lookups very fast with high probability.