The scientific article seems to be open access [1].
Before people draw links to recent large language model breakthroughs: Although they do use techniques from computational linguistics, there are no neural networks involved. This is more like old-school AI.
They have essentially a giant optimization problem, and they (approximately) model it as a lattice parsing problem, with a stochastic context-free grammar. They can solve that to optimality in O(n^3), which is too slow for some applications. So they propose a O(n) heuristic (hence no optimality guarantees, but the model was approximate to begin with anyways, and the heuristic is a lot faster), which is the reason for the name of their code: "LinearDesign".
Before people draw links to recent large language model breakthroughs: Although they do use techniques from computational linguistics, there are no neural networks involved. This is more like old-school AI.
They have essentially a giant optimization problem, and they (approximately) model it as a lattice parsing problem, with a stochastic context-free grammar. They can solve that to optimality in O(n^3), which is too slow for some applications. So they propose a O(n) heuristic (hence no optimality guarantees, but the model was approximate to begin with anyways, and the heuristic is a lot faster), which is the reason for the name of their code: "LinearDesign".
[1] https://www.nature.com/articles/s41586-023-06127-z