research
Researchers map LLM reasoning as geometric flows in representation space
A new geometric framework models how large language models reason through embedding trajectories that evolve like physical flows. Researchers tested whether LLMs internalize logic beyond surface form by using identical logical propositions with varied semantic content, finding evidence that next-token prediction training leads models to encode logical invariants as higher-order geometry.