From the 1 of 27 linked papers with an AI index.
27 papers
Native Video-Action Pretraining for Generalizable Robot Control
Qihang Zhang, Lin Li, Luyao Zhang +26
The paper introduces LingBot-VA 2.0, a video-action foundation model designed specifically for robot control, featuring a semantic visual-action tokenizer, causal pretraining, a sp…
Gaussians on a Diet: High-Quality Memory-Bounded 3D Gaussian Splatting Training
Yangming Zhang, Jian Xu, Chaojian Li +7
3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gaussian primitives. However, it…
A Survey of Neural Network Variational Monte Carlo from a Computing Workload Characterization Perspective
Zhengze Xiao, Xuanzhe Ding, Yuyang Lou +2
Neural Network Variational Monte Carlo (NNVMC) has emerged as a promising paradigm for solving quantum many-body problems by combining variational Monte Carlo with expressive neura…
From Inference Efficiency to Embodied Efficiency: Revisiting Efficiency Metrics for Vision-Language-Action Models
Zhuofan Li, Hongkun Yang, Zhenyang Chen +4
Vision-Language-Action (VLA) models have recently enabled embodied agents to perform increasingly complex tasks by jointly reasoning over visual, linguistic, and motor modalities.…
Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training
Lexington Whalen, Zhenbang Du, Haoran You +4
Training diffusion models (DMs) requires substantial computational resources due to multiple forward and backward passes across numerous timesteps, motivating research into efficie…
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
Chaojian Li, Zhifan Ye, Massimiliano Lupo Pasini +4
Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property…