Google DeepMind's latest research finds that large language models have difficulty autonomously correcting reasoning errors. The study found that models often err when trying to correct their initial responses solely based on their own judgment. The researchers believe that in currently sensitive safety scenarios, self-correction capabilities are essential. Achieving consensus responses through voting can ensure consistency but is not equivalent to self-correction. Further research is needed to improve the self-correction abilities of language models.