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The controllability of generative systems is typically mitigated through two types of mechanisms: reinforcement learning alignment (RLHF/RLAIF) and deterministic constraint layers.
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9/13/2026
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VerifiedRLHF is essentially a behavioral-level constraint that does not alter the model's underlying capabilities; models trained with RLHF still retain latent knowledge of the restricted behaviors.77% similarUnverified基于人类反馈的强化学习（RLHF）可一定程度减少主动欺骗性输出，宪法AI通过内置原则约束输出边界76% similarUnverified指令微调和RLHF强化了模型的指令跟随倾向，使其在提升任务能力的同时更易被外部指令误导75% similarUnverifiedSome systems embed safety preferences into model weights during the training phase through RLHF (Reinforcement Learning from Human Feedback), causing the model itself to tend to refuse generating certain content rather than relying on external filtering.74% similarUnverifiedRLHF的人类介入发生在训练阶段并固化为模型权重，属于隐式编码，而表征工程干预在推理时操控内部表征，具有即时性和可逆性74% similar
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