21 citations · 21 across the 1 of their papers we have counts for
3 papers
cs.AI2023★ 21 cited
Safe RLHF: Safe Reinforcement Learning from Human Feedback
Josef Dai, Xuehai Pan, Ruiyang Sun +5
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 tensio…
cs.AI2023
Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Jiaming Ji, Borong Zhang, Jiayi Zhou +7
Artificial intelligence (AI) systems possess significant potential to drive societal progress. However, their deployment often faces obstacles due to substantial safety concerns. S…
cs.CL2023
Baichuan 2: Open Large-scale Language Models
Aiyuan Yang, Bin Xiao, Bingning Wang +52
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing…