The Illusion of Superposition? A Principled Analysis of Latent Thinking in Language Models
Latent reasoning via continuous chain-of-thoughts (Latent CoT) has emerged as a promising alternative to discrete CoT reasoning. Operating in continuous space increases expressivity and has been hypothesized to enable superposition: the ability to maintain multiple candidate solutions simultaneously within a single representation. Despite theoretical arguments, it remains unclear whether language models actually leverage superposition when reasoning using latent CoTs. We investigate this question across three regimes: a training-free regime that constructs latent thoughts as convex combinations of token embeddings, a fine-tuned regime where a base model is adapted to produce latent though...
| Authors | Michael Rizvi-Martel, Guillaume Rabusseau, Marius Mosbach |
|---|---|
| Primary category | cs.CL |
| Published | 7 April 2026 |
| Last updated at source | 3 August 2026 |
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