Unverified70% confidenceFactExact time
By externalizing intermediate steps as text, chain-of-thought equivalently extends the model's effective computational depth from the number of layers in a single forward pass to the number of layers multiplied by the number of reasoning steps.
2
Sources
70%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
UnverifiedIn deep thinking mode, the model first generates intermediate reasoning steps internally, then derives the final conclusion based on those steps, performing significantly better than direct generation when handling multi-step logical reasoning tasks.83% similarUnverifiedDuring inference, the model processes input triplets group by group in an autoregressive manner along the depth axis.78% similarUnverifiedDeep recursive reasoning models refer to a class of neural network architectures that gradually refine internal representations through multiple iterations of forward computation.78% similarVerifiedChain of Thought能显著提升模型在数学推理、逻辑判断等需要多步推导的任务上的表现77% similarUnverifiedRecurrent depth is more likely to complement chain-of-thought rather than fully replace it, and a hybrid architecture can be adopted: first performing multiple rounds of silent computation in latent space, then outputting a refined reasoning chain or final answer.77% similar
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