helpness 和 harmless之间有一定冲突,但大模型上这种问题会缓解,甚至对于helpful和harmless training data的比例更加鲁棒。 在不需要任何有伤害的样本,我们展示了OOD detection技术去拒绝更多奇怪和伤害的request。 Scaling, RLHF Robustness, and Iterated ‘Online’ Training Reward model 准确率是按照model和dataset的lo...
二、Dataset 2.1 特定Task和众包 2.2 Helpful 和 Harmless数据集 2.3 用于跟接口反馈的模型 2.4 基于Elo Score比较模型 三、偏好建模 3.1 Models 3.2 Scaling 3.3 Calibration of Preference Models and Implications for RL 3.4 Evaluating 四、RLHF 4.4 Helpful vs Harmless 冲突 Figure 14: 原文:arxiv.org/abs/...
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Claude differs from other models in that it is trained and conditioned to adhere to a 73-point “Constitutional AI” framework designed to render the AI’s responses both helpful and harmless. Claude is first trained through a supervised learning method wherein the model will generate a response...
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback https://arxiv.org/abs/2204.05862 https://github.com/anthropics/hh-rlhf ★★★ 我们应用偏好建模和来自人类反馈的强化学习(RLHF)来微调语言模型,以充当有用和无害的助手。我们发现,这种对齐训练可以提高几乎所有NLP评估...