1 citations · 1 across the 6 of their papers we have counts for
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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…
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…
InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization
Haoxiang Ma, Junhao Cai, Xiaoxu Xu +26
Unified models for robot manipulation aim to equip one policy with both the semantic priors of pretrained VLMs and the physical dynamics learned through future prediction. In pract…
EBench: Elemental Diagnosis of Generalist Mobile Manipulation Policies
Ning Gao, Jinliang Zheng, Xing Gao +22
We present EBench, a simulation benchmark that diagnoses generalist mobile manipulation policies beyond a single success-rate scalar. EBench comprises 26 diverse and challenging ma…