Reinforcement learning from human feedback (RLHF) is a variant of reinforcement learning (RL) that learns from human feedback instead of relying on an engineered reward function …
Reinforcement learning from human feedback (RLHF) has proven effective in aligning large language models (LLMs) with human preferences. However, gathering high-quality human …
J Dai, X Pan, R Sun, J Ji, X Xu, M Liu, Y Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
With the development of large language models (LLMs), striking a balance between the performance and safety of AI systems has never been more critical. However, the inherent …
Reinforcement learning from human feedback (RLHF) has become a pivot technique in aligning large language models (LLMs) with human preferences. In RLHF practice …
AI alignment in the shape of Reinforcement Learning from Human Feedback (RLHF) is increasingly treated as a crucial ingredient for high performance large language …
This study is an empirical investigation into the semantic vulnerabilities of four popular pre- trained commercial Large Language Models (LLMs) to ideological manipulation. Using …
Reinforcement Learning from Human Feedback (RLHF) facilitates the alignment of large language models with human preferences, significantly enhancing the quality of interactions …
Large language models (LLMs) have formulated a blueprint for the advancement of artificial general intelligence. Its primary objective is to function as a human-centric (helpful, honest …
B Wang, R Zheng, L Chen, Y Liu, S Dou… - arXiv preprint arXiv …, 2024 - arxiv.org
Reinforcement Learning from Human Feedback (RLHF) has become a crucial technology for aligning language models with human values and intentions, enabling models to …