2 citations · 8 across the 13 of their papers we have counts for
13 papers
PhysMem: Scaling Test-Time Memory for Embodied Physical Reasoning
Haoyang Li, Yang You, Hao Su +1
Reliable object manipulation requires understanding physical properties that vary across objects and environments. Vision-language model (VLM) planners can reason about friction an…
Mull-Tokens: Modality-Agnostic Latent Thinking
Arijit Ray, Ahmed Abdelkader, Chengzhi Mao +5
Reasoning goes beyond language; the real world requires reasoning about space, time, affordances, and much more that words alone cannot convey. Existing multimodal models exploring…
Rodrigues Network for Learning Robot Actions
Jialiang Zhang, Haoran Geng, Yang You +4
Understanding and predicting articulated actions is important in robot learning. However, common architectures such as MLPs and Transformers lack inductive biases that reflect the…
Denoising Hamiltonian Network for Physical Reasoning
Congyue Deng, Brandon Y. Feng, Cecilia Garraffo +5
Machine learning frameworks for physical problems must capture and enforce physical constraints that preserve the structure of dynamical systems. Many existing approaches achieve t…
Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning
Yang You, Yixin Li, Congyue Deng +2
Vision foundation models, particularly the ViT family, have revolutionized image understanding by providing rich semantic features. However, despite their success in 2D comprehensi…
Neural Attention Field: Emerging Point Relevance in 3D Scenes for One-Shot Dexterous Grasping
Qianxu Wang, Congyue Deng, Tyler Ga Wei Lum +5
One-shot transfer of dexterous grasps to novel scenes with object and context variations has been a challenging problem. While distilled feature fields from large vision models hav…
D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation
Songlin Wei, Haoran Geng, Jiayi Chen +6
Depth sensing is an important problem for 3D vision-based robotics. Yet, a real-world active stereo or ToF depth camera often produces noisy and incomplete depth which bottlenecks…
ARCH: Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly
Jiankai Sun, Aidan Curtis, Yang You +8
Generalizable long-horizon robotic assembly requires reasoning at multiple levels of abstraction. While end-to-end imitation learning (IL) is a promising approach, it typically req…
PhysPart: Physically Plausible Part Completion for Interactable Objects
Rundong Luo, Haoran Geng, Congyue Deng +5
Interactable objects are ubiquitous in our daily lives. Recent advances in 3D generative models make it possible to automate the modeling of these objects, benefiting a range of ap…
RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation
Yuxuan Kuang, Junjie Ye, Haoran Geng +5
This work proposes a retrieve-and-transfer framework for zero-shot robotic manipulation, dubbed RAM, featuring generalizability across various objects, environments, and embodiment…
CAD: Photorealistic 3D Generation via Adversarial Distillation
Ziyu Wan, Despoina Paschalidou, Ian Huang +5
The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of the…
SAGE: Bridging Semantic and Actionable Parts for GEneralizable Manipulation of Articulated Objects
Haoran Geng, Songlin Wei, Congyue Deng +3
To interact with daily-life articulated objects of diverse structures and functionalities, understanding the object parts plays a central role in both user instruction comprehensio…
Make a Donut: Hierarchical EMD-Space Planning for Zero-Shot Deformable Manipulation with Tools
Yang You, Bokui Shen, Congyue Deng +4
Deformable object manipulation stands as one of the most captivating yet formidable challenges in robotics. While previous techniques have predominantly relied on learning latent d…