117 citations · 327 across the 26 of their papers we have counts for
5 papers · 1 filter
Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein Simulators
Jingbang Chen, Yian Wang, Xingwei Qu +4
Molecular dynamics simulations have emerged as a fundamental instrument for studying biomolecules. At the same time, it is desirable to perform simulations of a collection of parti…
Learning Semantic-Agnostic and Spatial-Aware Representation for Generalizable Visual-Audio Navigation
Hongcheng Wang, Yuxuan Wang, Fangwei Zhong +4
Visual-audio navigation (VAN) is attracting more and more attention from the robotic community due to its broad applications, \emph{e.g.}, household robots and rescue robots. In th…
Learning a Universal Human Prior for Dexterous Manipulation from Human Preference
Zihan Ding, Yuanpei Chen, Allen Z. Ren +4
Generating human-like behavior on robots is a great challenge especially in dexterous manipulation tasks with robotic hands. Scripting policies from scratch is intractable due to t…
PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observations
Haoran Geng, Ziming Li, Yiran Geng +3
Learning a generalizable object manipulation policy is vital for an embodied agent to work in complex real-world scenes. Parts, as the shared components in different object categor…
Learning Foresightful Dense Visual Affordance for Deformable Object Manipulation
Ruihai Wu, Chuanruo Ning, Hao Dong
Understanding and manipulating deformable objects (e.g., ropes and fabrics) is an essential yet challenging task with broad applications. Difficulties come from complex states and…