6 citations · 15 across the 9 of their papers we have counts for
6 papers · 1 filter
MRJ-Agent: An Effective Jailbreak Agent for Multi-Round Dialogue
Fengxiang Wang, Ranjie Duan, Peng Xiao +9
Large Language Models (LLMs) demonstrate outstanding performance in their reservoir of knowledge and understanding capabilities, but they have also been shown to be prone to illega…
ManiBox: Enhancing Embodied Spatial Generalization via Scalable Simulation Data Generations
Hengkai Tan, Xuezhou Xu, Chengyang Ying +7
Embodied agents require robust spatial intelligence to execute precise real-world manipulations. However, this remains a significant challenge, as current methods often struggle to…
RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
Songming Liu, Lingxuan Wu, Bangguo Li +6
Bimanual manipulation is essential in robotics, yet developing foundation models is extremely challenging due to the inherent complexity of coordinating two robot arms (leading to…
Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
Hengkai Tan, Songming Liu, Kai Ma +4
Transformer has shown promise in reinforcement learning to model time-varying features for obtaining generalized low-level robot policies on diverse robotics datasets in embodied l…
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
Zhongkai Hao, Chang Su, Songming Liu +6
Pre-training has been investigated to improve the efficiency and performance of training neural operators in data-scarce settings. However, it is largely in its infancy due to the…
Preconditioning for Physics-Informed Neural Networks
Songming Liu, Chang Su, Jiachen Yao +4
Physics-informed neural networks (PINNs) have shown promise in solving various partial differential equations (PDEs). However, training pathologies have negatively affected the con…