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  ## What is cool
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  The base verifier has fixed weights, but its inference process is not exhausted by ordinary left-to-right decoding. A learned continuous proposer can search for hidden-state trajectories and token paths that the verifier can recognize as correct, even if the verifier would rarely or never reach them under standard autoregressive rollout.
 
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+ ## How it was envisaged
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+ A machine for constructing candidate inner-machines that bias the verifier toward solution paths its default rollout would miss
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  ## What is cool
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  The base verifier has fixed weights, but its inference process is not exhausted by ordinary left-to-right decoding. A learned continuous proposer can search for hidden-state trajectories and token paths that the verifier can recognize as correct, even if the verifier would rarely or never reach them under standard autoregressive rollout.