LLM Latent Reasoning as Chain of Superposition
Models latent reasoning as a sequence of superposed token distributions and trains the process with supervised fine-tuning.
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arXiv:2510.15522 · Initial submission: 2025-10-17
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Continuous-state reasoning — Use vectors—lists of numbers—to carry intermediate reasoning from one step to the next, instead of selecting a text token at every step. Some methods use the model's hidden states; others combine several candidate token representations.
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