Verified65% confidenceFactExact time
After reinforcement learning from human feedback (RLHF), mainstream large language models naturally tend to produce satisfying and easily accepted responses rather than actively raising criticisms
3
Sources
65%
Confidence
Long-term
Relevance
9/12/2026
First Seen
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Unverified早期经RLHF训练的大型语言模型倾向于给出用户喜欢的回答，产生迎合性偏差（sycophancy）78% similarUnverifiedThe training objective of current large language models is to generate responses that satisfy the user, not to generate correct responses.76% similarUnverifiedDuring the RLHF stage, large language models are often optimized toward a highly interactive and fast-paced assistant-style conversational style.73% similarUnverified纠正性反馈对语言习得至关重要，学习者只有在尝试表达、犯错并获得及时校正的循环中才能内化语言规则70% similarUnverifiedLong's Interaction Hypothesis emphasizes that receiving corrective feedback during meaningful interaction is a key mechanism for language development.70% similar
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