3 accepted papers
Embodied agents must reason causally, as correlation-based models fail under intervention and distribution shift. This challenge arises in domains like robotics and cyber-physical systems, where agents balance efficiency and comfort under uncertainty. We introduce POLICYGRID, unifying causal discove
Visual autoregressive modeling has recently demonstrated potential in image tasks by enabling coarse-to-fine, next-level prediction. Most indoor 3D occupancy prediction methods, however, continue to rely on dense voxel grids and convolution-heavy backbones, which incur high computational costs when…
In many event detection applications, training data may contain tags with multiple, simultaneous events. This is particularly likely when the definition of “event” is broad and includes events that can persist for an extended period of time. Decomposing a mixed signal into signals corresponding to i…