1 citations · 1 across the 10 of their papers we have counts for
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Sensing Which Modality Matters: Evidence-Gated Regularization for Robust VLA Policies
Yue Yang, Diego Romeres, Chiori Hori +3
Vision-Language-Action (VLA) policies fuse multimodal sensory inputs, but training on limited and homogeneous robot demonstrations encourages spurious inter-sensor correlations rat…
Comparative Evaluation of 3D Reconstruction Methods for Immersive Visualization of Laboratory Objects
Brian De La Cruz, Aaron Y. Zhao, Maitrey Gramopadhye +4
In this study, we examined whether current 3D reconstruction methods can support the creation of realistic holographic representations of laboratory objects for educational use. In…
DenseReward: Dense Reward Learning via Failure Synthesis for Robotic Manipulation
Yu Fang, Wanxi Dong, Jiaqi Liu +7
Reinforcement learning holds great promise for improving robot policies beyond the limits of imitation learning. However, its practical adoption remains bottlenecked by the lack of…
Current as Touch: Proprioceptive Contact Feedback for Compliant Dexterous Manipulation
Chenyang Ma, Yunchao Yao, Zhenyu Wei +3
Compliance is essential for dexterous manipulation, yet existing solutions often rely on external tactile or force sensors that are costly, fragile, and difficult to deploy on low-…
When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs
Yu Fang, Yuchun Feng, Dong Jing +5
Vision-Language-Action models (VLAs) promise to ground language instructions in robot control, yet in practice often fail to faithfully follow language. When presented with instruc…