How do LLMs perform reasoning without explicit symbolic logic?

LLMs simulate reasoning through pattern learning over large corpora of structured text.

LLMs do not implement symbolic reasoning engines but approximate reasoning via statistical pattern completion. Chain-of-thought prompting and intermediate latent representations help models simulate stepwise reasoning. However, this is fragile and can fail under distribution shift or adversarial prompts.