Chain-of-thought prompting is rationalization, not true reasoning

By PulseAugur Editorial · [1 sources] · 2026-07-22 17:24

Chain-of-thought prompting is a technique where a language model generates text that increases the likelihood of a correct answer, which it then presents as its reasoning process. While this method is useful, the generated text is a rationalization created before the final conclusion, rather than an explanation of how the conclusion was reached. AI

IMPACT Clarifies the distinction between generated rationalizations and actual model reasoning processes.

RANK_REASON The item is an opinion piece discussing the nature of chain-of-thought prompting in LLMs.

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Chain-of-thought prompting is rationalization, not true reasoning

COVERAGE [1]

Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] · 2026-07-22 17:24

Chain-of-thought isn't the model reasoning. It's the model generating text that raises the odds of a right answer, then narrating it as reasoning. Useful. But y

Chain-of-thought isn't the model reasoning. It's the model generating text that raises the odds of a right answer, then narrating it as reasoning. Useful. But you're reading a rationalization written before the conclusion, not after. # AI # MachineLearning # LLM # Threadverse # T…

COVERAGE [1]

Chain-of-thought isn't the model reasoning. It's the model generating text that raises the odds of a right answer, then narrating it as reasoning. Useful. But y

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