127 citations · 202 across the 7 of their papers we have counts for
7 papers
A Good Plan is Hard to Find: Aligning Models with Preferences is Misaligned with What Helps Users
Nishant Balepur, Matthew Shu, Yoo Yeon Sung +5
To assist users in complex tasks, LLMs generate plans: step-by-step instructions towards a goal. While alignment methods aim to ensure LLM plans are helpful, they train (RLHF) or e…
RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models
Bang An, Shiyue Zhang, Mark Dredze
Efforts to ensure the safety of large language models (LLMs) include safety fine-tuning, evaluation, and red teaming. However, despite the widespread use of the Retrieval-Augmented…
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…
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…
BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
Jiaming Ji, Mickel Liu, Juntao Dai +6
In this paper, we introduce the BeaverTails dataset, aimed at fostering research on safety alignment in large language models (LLMs). This dataset uniquely separates annotations of…
OmniSafe: An Infrastructure for Accelerating Safe Reinforcement Learning Research
Jiaming Ji, Jiayi Zhou, Borong Zhang +7
AI systems empowered by reinforcement learning (RL) algorithms harbor the immense potential to catalyze societal advancement, yet their deployment is often impeded by significant s…
Proactive Multi-Camera Collaboration For 3D Human Pose Estimation
Hai Ci, Mickel Liu, Xuehai Pan +2
This paper presents a multi-agent reinforcement learning (MARL) scheme for proactive Multi-Camera Collaboration in 3D Human Pose Estimation in dynamic human crowds. Traditional fix…