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cs.LG2024
Correcting Large Language Model Behavior via Influence Function
Han Zhang, Zhuo Zhang, Yi Zhang +8
Recent advancements in AI alignment techniques have significantly improved the alignment of large language models (LLMs) with static human preferences. However, the dynamic nature…
cs.LG2024
COPR: Continual Human Preference Learning via Optimal Policy Regularization
Han Zhang, Lin Gui, Yu Lei +8
Reinforcement Learning from Human Feedback (RLHF) is commonly utilized to improve the alignment of Large Language Models (LLMs) with human preferences. Given the evolving nature of…
cs.LG2024
COPR: Continual Learning Human Preference through Optimal Policy Regularization
Han Zhang, Lin Gui, Yuanzhao Zhai +3
The technique of Reinforcement Learning from Human Feedback (RLHF) is a commonly employed method to improve pre-trained Language Models (LM), enhancing their ability to conform to…