arXiv:2605.24850v1 Announce Type: new Abstract: Evaluating whether large language models (LLMs) capture the structure of natural language beyond local fluency remains an open challenge. Existing evaluation methods, largely based on task performance or short-context behavior, provide limited insight into the long-range statistical organization of generated text. We propose a complementary evaluation framework based on repeated subsequences. By analyzing their distribution across scales and relating it to higher-order R\'enyi entropies, we probe how texts reuse previously established structure u
Source: arXiv cs.CL — read the full report at the original publisher.