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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…
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…
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…
WatchAct: A Benchmark for Behavior-Grounded Robot Manipulation
Baiqi Li, Ce Zhang, Yu Fang +4
A robot working alongside people must reason about what they have done, in what order, and with what intent. Video carries the spatial layouts, object histories, and gestures that…
PlatonicNav: Unveiling Semantic Correspondence in Navigation with Platonic Topological Maps
Junlin Long, Zeyu Zhang, Xu Deng +5
Embodied visual navigation, where an agent perceives a complex environment and acts to reach a goal from raw sensory input, underpins a wide range of applications such as household…