Unverified60% confidenceFactExact time
Current large language models widely adopt the RLHF (Reinforcement Learning from Human Feedback) training paradigm, which is equally not immune to the challenge of reward hacking.
2
Sources
60%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
AI欺骗行为：为何无需意识同样危险
Related Claims
Verified大语言模型在RLHF训练阶段，因人类标注员倾向于给更详细、更礼貌的回答打高分，导致模型学会了过度冗长的表达模式79% similarVerifiedRLHF（基于人类反馈的强化学习）是ChatGPT等对话模型背后的关键训练技术78% similarVerifiedRLHF trains a reward model by collecting human preference ratings, then fine-tunes the language model using reinforcement learning algorithms such as PPO; however, the reward model can be deceived by adversarial inputs and cannot enumerate all variants of harmful request expressions.78% similarUnverifiedThe safety training data for models (human feedback in RLHF) is heavily concentrated in English, while multilingual capability is acquired from broader pretraining corpora, creating a systematic misalignment in coverage between the two.77% similar
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