126 citations · 388 across the 24 of their papers we have counts for
7 papers · 1 filter
WA-JEPA: Rethinking the Video JEPA Paradigm for World-Action Modeling in Autonomous Driving
Xinlin Wang, Yujiao Xiang, Yuheng Zhou +11
Video Joint Embedding Predictive Architecture (V-JEPA) learns powerful spatiotemporal representations from video through self-supervised latent feature prediction. However, V-JEPA…
EvoStreaming: Your Offline Video Model Is a Natively Streaming Assistant
Zichen Wen, Boxue Yang, Junlong Ke +5
Streaming video understanding demands more than watching longer videos: assistants must decide when to speak in real time, balancing responsiveness against verbosity. Yet most vide…
CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving
Minqing Huang, Yujiao Xiang, Zihan Liang +8
Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing reasoning mechanisms still struggle to provide plannin…
Exploring Long Tail Visual Relationship Recognition with Large Vocabulary
Sherif Abdelkarim, Aniket Agarwal, Panos Achlioptas +5
Several approaches have been proposed in recent literature to alleviate the long-tail problem, mainly in object classification tasks. In this paper, we make the first large-scale s…
LDMNet: Low Dimensional Manifold Regularized Neural Networks
Wei Zhu, Qiang Qiu, Jiaji Huang +3
Deep neural networks have proved very successful on archetypal tasks for which large training sets are available, but when the training data are scarce, their performance suffers f…
GraphConnect: A Regularization Framework for Neural Networks
Jiaji Huang, Qiang Qiu, Robert Calderbank +1
Deep neural networks have proved very successful in domains where large training sets are available, but when the number of training samples is small, their performance suffers fro…
Geometry-aware Deep Transform
Jiaji Huang, Qiang Qiu, Robert Calderbank +1
Many recent efforts have been devoted to designing sophisticated deep learning structures, obtaining revolutionary results on benchmark datasets. The success of these deep learning…