ThinkRouter: Efficient Reasoning via Routing Thinking between Latent and Discrete Spaces
Routes intermediate computation between latent and discrete representations to trade off reasoning quality, readability, and token cost.
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arXiv:2602.11683 · Initial submission: 2026-02-12
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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.
Thinking tokens — Give a model extra tokens for computation, such as pauses, filler symbols, or learned planning tokens. These tokens need not spell out the solution.
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