7 citations · 12 across the 11 of their papers we have counts for
11 papers
MANIGUARD: A Benchmark and Data Suite for Specification-Grounded Safety Evaluation and Improvement of Robotic Manipulation
Yiyan Peng, Philip Wang, Simon Sinong Zhan +11
Foundation-model policies for robotic manipulation are advancing rapidly on task success, but rigorous evaluation of whether they succeed safely is still lacking. We introduce Mani…
Skills in Weights, Memory in Code: Hybrid Learning for Memory-Dependent Robot Manipulation
Yunhao Zhao, Zhenyang Ni, Haoyang Chen +2
Modern vision-language-action (VLA) policies have acquired broad manipulation skills, but typically generate each action chunk from the current observation or a short fixed-length…
CreFlow: Corrective Reflow for Sparse-Reward Embodied Video Diffusion RL
Zhenyang Ni, Yijiang Li, Ruochen Jiao +7
Video generation models trained on heterogeneous data with likelihood-surrogate objectives can produce visually plausible rollouts that violate physical constraints in embodied man…
EmboAlign: Aligning Video Generation with Compositional Constraints for Zero-Shot Manipulation
Gehao Zhang, Zhenyang Ni, Payal Mohapatra +3
Video generative models (VGMs) pretrained on large-scale internet data can produce temporally coherent rollout videos that capture rich object dynamics, offering a compelling found…
Self-Localized Collaborative Perception
Zhenyang Ni, Zixing Lei, Yifan Lu +4
Collaborative perception has garnered considerable attention due to its capacity to address several inherent challenges in single-agent perception, including occlusion and out-of-r…
Robust Collaborative Perception without External Localization and Clock Devices
Zixing Lei, Zhenyang Ni, Ruize Han +5
A consistent spatial-temporal coordination across multiple agents is fundamental for collaborative perception, which seeks to improve perception abilities through information excha…
Physical Backdoor Attack can Jeopardize Driving with Vision-Large-Language Models
Zhenyang Ni, Rui Ye, Yuxi Wei +3
Vision-Large-Language-models(VLMs) have great application prospects in autonomous driving. Despite the ability of VLMs to comprehend and make decisions in complex scenarios, their…
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation
Rui Ye, Yaxin Du, Zhenyang Ni +2
In federated learning (FL), data heterogeneity is one key bottleneck that causes model divergence and limits performance. Addressing this, existing methods often regard data hetero…
FedFM: Anchor-based Feature Matching for Data Heterogeneity in Federated Learning
Rui Ye, Zhenyang Ni, Chenxin Xu +3
One of the key challenges in federated learning (FL) is local data distribution heterogeneity across clients, which may cause inconsistent feature spaces across clients. To address…
Aware of the History: Trajectory Forecasting with the Local Behavior Data
Yiqi Zhong, Zhenyang Ni, Siheng Chen +1
The historical trajectories previously passing through a location may help infer the future trajectory of an agent currently at this location. Despite great improvements in traject…
GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning
Chenxin Xu, Maosen Li, Zhenyang Ni +2
Demystifying the interactions among multiple agents from their past trajectories is fundamental to precise and interpretable trajectory prediction. However, previous works only con…