思维链是让大语言模型在给出结论前先输出中间推理步骤的提示与推理方式，核心是把不可见的内部计算转成可读可检的文本过程，能力包括分步提示、多路径采样与推理链回溯。它解决的是复杂推理任务上结果不可信、出错环节无法定位的问题，并不解决模型基础能力不足导致的推理天花板问题。
思维链的核心是过程外显，它可以帮助企业实现以下目标：
- 让推理依据可被检查。中间步骤以文本呈现，审查者能看出推理在哪一环出现偏差。提示模板中显式要求模型分步思考，输出结构因此稳定，中间步骤可以交由规则或另一个模型做自动校验。
- 让复杂问题被分解处理。多步推理把大任务拆成若干小判断，每步输出成为下一步输入。推理链被完整保留后，失败案例可以回溯到具体环节，改进方向从重新训练模型收敛为调整提示或校验逻辑。
- 让错误可以定位到具体环节。是哪一步推理失效可以被指出，而不是只知最终答案不对。
- 让同一问题得到多条解法。多次采样产生不同推理路径，可横向比对哪条更可靠。
总之，思维链可以帮助企业实现复杂推理任务从只给结论到过程可查的转变，把推理质量问题转化为可定位、可改进的具体环节，降低高风险场景依赖模型输出的不确定性，让推理能力的评估与提升都有明确抓手。
翻译
Chain-of-thought is the prompting and reasoning approach of having a large language model emit intermediate reasoning steps before reaching a conclusion. Its core is turning invisible internal computation into readable and inspectable textual process, with capabilities covering step-wise prompting, multi-path sampling and reasoning-chain retrospection. It solves the problems of results being untrustworthy on complex reasoning tasks and of errors that cannot be located, but it does not solve the reasoning ceiling imposed by insufficient underlying model capability.
At the heart of chain-of-thought is making the process external, which can help companies achieve the following:
- Make reasoning grounds checkable. Intermediate steps appear as text, allowing reviewers to see exactly where reasoning diverged.
- Break complex problems apart. Multi-step reasoning divides a large task into several small judgments, each output becoming the next input.
- Localize errors to specific steps. The step where reasoning failed can be pointed out rather than only knowing the final answer is incorrect.
- Get multiple solutions to one question. Repeated sampling produces different reasoning paths, and the more reliable path can be identified by comparison.
In short, chain-of-thought can help enterprises shift complex reasoning tasks from producing conclusions only to having a checkable process, turn reasoning quality problems into specific locatable and improvable points, reduce reliance uncertainty on model output in high-risk scenarios, and give both evaluation and improvement of reasoning capability a clear handle.
