Do LLMs Understand Sequential Structure? A Controlled Study of Inference and Generation

Excerpt

arXiv:2610.04977v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as interactive agents and simulators, yet it remains unclear whether they can recover latent sequential structure beyond surface action frequencies. This distinction is critical for behavioral simulation, where actions are often shaped by prior context rather than marginal frequencies alone. We study this question using controlled two-player Rock--Paper--Scissors interactions and a one-player stoch