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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…
FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model
Chenyang Ma, Yue Yang, Radu Corcodel +4
Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduce FurnitureVLA, the first systematic study of real-scale bimanu…
Velocity Potential Neural Field for Efficient Ambisonics Impulse Response Modeling
Yoshiki Masuyama, Francois G. Germain, Gordon Wichern +2
First-order Ambisonics (FOA) is a standard spatial audio format based on spherical harmonic decomposition. Its zeroth- and first-order components capture the sound pressure and par…
Embedding Morphology into Transformers for Cross-Robot Policy Learning
Kei Suzuki, Jing Liu, Ye Wang +4
Cross-robot policy learning -- training a single policy to perform well across multiple embodiments -- remains a central challenge in robot learning. Transformer-based policies, su…