Explained: Why Chain of Thought (CoT) Actually Works in LLMs
NaveenGRao · x · 2026-08-05
The post quotes @lujasper's deep insights into why Chain of Thought (CoT) works. The author explains that during initial inference, the correct reasoning paths already exist as probabilities within the model's hidden states.
However, standard token sampling is destructive—materializing the wrong token can instantly drop a 30% probability of reaching the right answer down to 0. CoT mitigates this because the model's constant backtracking (using words like "wait" or "but") provides multiple chances to correct its trajectory and hit the target path.
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