34 citations · 61 across the 7 of their papers we have counts for
7 papers
Finding Kissing Numbers with Game-theoretic Reinforcement Learning
Chengdong Ma, Théo Tao Zhaowei, Pengyu Li +7
Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a central sphere has remained a defining chall…
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
Kun Wang, Guibin Zhang, Zhenhong Zhou +100
The remarkable success of Large Language Models (LLMs) has illuminated a promising pathway toward achieving Artificial General Intelligence for both academic and industrial communi…
Theoretically Guaranteed Policy Improvement Distilled from Model-Based Planning
Chuming Li, Ruonan Jia, Jie Liu +5
Model-based reinforcement learning (RL) has demonstrated remarkable successes on a range of continuous control tasks due to its high sample efficiency. To save the computation cost…
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…
Heterogeneous Value Alignment Evaluation for Large Language Models
Zhaowei Zhang, Ceyao Zhang, Nian Liu +5
The emergent capabilities of Large Language Models (LLMs) have made it crucial to align their values with those of humans. However, current methodologies typically attempt to assig…
UniDexGrasp++: Improving Dexterous Grasping Policy Learning via Geometry-aware Curriculum and Iterative Generalist-Specialist Learning
Weikang Wan, Haoran Geng, Yun Liu +4
We propose a novel, object-agnostic method for learning a universal policy for dexterous object grasping from realistic point cloud observations and proprioceptive information unde…
Heterogeneous-Agent Reinforcement Learning
Yifan Zhong, Jakub Grudzien Kuba, Xidong Feng +3
The necessity for cooperation among intelligent machines has popularised cooperative multi-agent reinforcement learning (MARL) in AI research. However, many research endeavours hea…