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Large Language Models (LLMs) are increasingly used as probabilistic generators for simulation, synthetic data generation, and decision support in settings where real-world data are unavailable. Yet, the structure and reliability of the distributions they produce remain understudied. Here, we systematically analyze LLM-...
The proposed percolation process displays a universal phase transition, characterized by the abrupt and simultaneous disappearance of both the giant connected component and the largest 2-core, across networks with markedly different degree distributions, indicating that the physics of network dismantling is insensitive...
This work considers the problem of finding, for a given degree sequence, the network structure displaying the smallest possible average shortest-path length and proposes a fast algorithm to construct approximate solutions to such a degree-constrained distance-minimization problem.
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