6 papers · 1 filter
PerturBot: Breaking Shortcut Priors in Vision-Language-Action Models with Perturbative Training
Mingyu Liu, Chonghao Sima, Tianjian Feng +4
A vision--language--action (VLA) policy can complete complex tasks while ignoring the evidence that should determine its actions. An object held near the wrist camera can displace…
A4A: Cross-Embodiment Transfer of Action-Oriented 4D Affordances from Human Demonstrations
Yifan Han, Litao Liu, Yuqi Gu +7
Human demonstrations contain rich manipulation knowledge, but it remains unclear what information can be transferred effectively to robot control. Existing affordance representatio…
Perfect Demo Makes Poor Teacher: Learning Robust Alignment from Critical Motion Segments
Mingyu Liu, Zeju Li, Jiuhe Shu +4
Expert demonstrations are widely assumed to be the gold standard for robot imitation learning. Yet for fine-grained manipulation such as insertion, stacking, and alignment, we unco…
Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation
Litao Liu, Yifan Han, Pengfei Yi +9
Task-conditioned manipulation requires grounding instructions to task-relevant functional parts rather than object categories. This setting is scene-dependent and often one-to-many…
Motion-Driven Multi-Object Tracking of Model Organisms in Space Science Experiments
Jianing You, Han Wang, Kang Liu +4
Automated animal behavior analysis relies on long-term, interpretable individual trajectories; however, multi-animal tracking in space science experimental videos remains highly ch…
FSAG: Enhancing Human-to-Dexterous-Hand Finger-Specific Affordance Grounding via Diffusion Models
Yifan Han, Yichuan Peng, Pengfei Yi +5
Dexterous grasp synthesis must jointly satisfy functional intent and physical feasibility, yet existing pipelines often decouple semantic grounding from refinement, yielding unstab…