arXiv Paper Examines Capacity Limits of Reasoning via Superposition

A new arXiv preprint studies how much intermediate computation a single vector can carry when language models reason through continuous or recurrent methods rather than token-by-token chain-of-thought. The work frames multi-step reasoning as superposition, where partial computations are packed into hidden states, and analyzes the resulting capacity limits. It offers a theoretical lens on the trade-offs between explicit token-based reasoning and continuous latent approaches.