引导式测验 · 中等 等级

思维链推理测验

比较工作示例和零样本提示，以及自我一致性、训练有素的推理、生成的步骤上下文和解释的忠实度。

相关引导路径思维链推理
问题 1 的 8

链式思考提示在引用的工作示例研究中引发了什么？

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  1. 链式思考提示在引用的工作示例研究中引发了什么？
    • A guarantee that every answer is logically correct
    • Only an unchanged database lookup identifier
    • Intermediate generated steps before a final answer
    • Automatic removal of all answer text
  2. 哪个简单的短语可以在没有示例的情况下触发逐步推理（零样本 CoT）？
    • “立即答复”
    • “简短一点”
    • “忽略这个问题”
    • “让我们一步一步思考”
  3. What scope applies to the original paper’s findings about scale and CoT gains?
    • They prove every small model can never reason
    • They concern the tasks and model sizes actually evaluated
    • They prove every larger model must improve on every task
    • They establish that prompting changes model weights immediately
  4. What does the cited self-consistency method aggregate after sampling different reasoning paths?
    • Their final answers
    • Only the alphabetical order of explanation words
    • Only one required greedy path
    • New model weights computed from each sampled answer
  5. How does the original DeepSeek-R1 report’s training study differ from supplying a fixed model with CoT prompt examples?
    • It proves all displayed reasoning is a faithful internal trace
    • It requires no model training of any kind
    • It changes every prompt into a permanent tokenizer entry
    • It trains reasoning behavior through RL and a stated staged pipeline
  6. In an autoregressive generated solution, how can an earlier step affect later generation?
    • It guarantees every later inference is correct
    • Its text can become context for subsequent tokens
    • It removes all attention to the original problem
    • It necessarily changes the model’s original weights
  7. What feature distinguishes few-shot CoT exemplars from answer-only exemplars in the original prompting comparison?
    • Intermediate solution steps are included with the example answers
    • Every example omits its question
    • The prompt must retrain the model weights
    • All exemplars are only random strings with no answers
  8. What did the cited unfaithful-explanation study show about some generated reasoning explanations?
    • They always reveal every true causal influence on the model
    • They prove every generated answer is false
    • They can omit biasing input influences while rationalizing the affected answer
    • They eliminate the need for external task verification