1 citations · 2 across the 7 of their papers we have counts for
7 papers
UniPixie: Unified and Probabilistic 3D Physics Learning via Flow Matching
Qilin Huang, Quynh Anh Huynh, Long Le +5
Existing feed-forward networks excel at predicting a single set of physical properties from visual appearance, but this point-estimate paradigm fundamentally fails to capture the r…
OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies
Yunzhou Song, Long Le, Yong-Hyun Park +7
Vision-language-action(VLA) models have shown great promise as generalist policies for a large range of relatively simple tasks. However, they demonstrate limited performance on mo…
Maestro: Orchestrating Robotics Modules with Vision-Language Models for Zero-Shot Generalist Robots
Junyao Shi, Rujia Yang, Kaitian Chao +9
Today's best-explored routes towards generalist robots center on collecting ever larger "observations-in actions-out" robotics datasets to train large end-to-end models, copying a…
Avi: Action from Volumetric Inference
Harris Song, Long Le
We propose Avi, a novel 3D Vision-Language-Action (VLA) architecture that reframes robotic action generation as a problem of 3D perception and spatial reasoning, rather than low-le…
Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels
Long Le, Ryan Lucas, Chen Wang +4
Inferring the physical properties of 3D scenes from visual information is a critical yet challenging task for creating interactive and realistic virtual worlds. While humans intuit…
Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
Long Le, Jason Xie, William Liang +7
Interactive 3D simulated objects are crucial in AR/VR, animations, and robotics, driving immersive experiences and advanced automation. However, creating these articulated objects…
Distributed Continual Learning
Long Le, Marcel Hussing, Eric Eaton
This work studies the intersection of continual and federated learning, in which independent agents face unique tasks in their environments and incrementally develop and share know…