6 papers
VLAQuantBench: Closed-Loop Evaluation of Post-Training Quantization for Vision-Language-Action Models
Jiuyi Xu, Qing Jin, Meida Chen +3
Post-training quantization reduces the memory requirements of vision-language-action (VLA) models, but precision selection must account for the interaction between layer scope, num…
Predict Before You Deploy: Offline Prediction of Quantization-Induced Task Degradation for World Action Models
Jiuyi Xu, Jinjia Guo, Meida Chen +2
World action models (WAMs) rely on video-generation backbones, requiring substantial memory and compute for deployment. Post-training quantization reduces memory and can accelerate…
LowDiff: Efficient Diffusion Sampling with Low-Resolution Condition
Jiuyi Xu, Qing Jin, Meida Chen +3
Diffusion models have achieved remarkable success in image generation but their practical application is often hindered by the slow sampling speed. Prior efforts of improving effic…
IDU: Incremental Dynamic Update of Existing 3D Virtual Environments with New Imagery Data
Meida Chen, Luis Leal, Yue Hu +5
For simulation and training purposes, military organizations have made substantial investments in developing high-resolution 3D virtual environments through extensive imaging and 3…
Open-Vocabulary High-Resolution 3D (OVHR3D) Data Segmentation and Annotation Framework
Jiuyi Xu, Meida Chen, Andrew Feng +2
In the domain of the U.S. Army modeling and simulation, the availability of high quality annotated 3D data is pivotal to creating virtual environments for training and simulations.…
To Shelter or Not To Shelter: Exploring the Influence of Different Modalities in Virtual Reality on Individuals' Tornado Mitigation Behaviors
Jiuyi Xu, Tolulope Sanni, Ziming Liu +4
Timely and adequate risk communication before natural hazards can reduce losses from extreme weather events and provide more resilient disaster preparedness. However, existing natu…