10 accepted papers
Traffic prediction serves as a cornerstone of modern intelligent transportation systems and the critical task of spatio-temporal forecasting. Although advanced Spatio-temporal Graph Neural Networks (STGNNs) and pre-trained models have made significant progress in traffic prediction, two critical ch
Irregular multivariate time series (IMTS), characterized by uneven sampling and inter-variate asynchrony, fuel many forecasting applications yet remain challenging to model efficiently. Canonical Pre-Alignment (CPA) has been widely adopted in IMTS modeling by padding zeros at every global timestamp,
This work focuses on enhancing computational efficiency in wide-band radio frequency (RF) imaging. Specifically, we aim to efficiently generate multispectral RF images that contain information on range, angle, and frequency-selected responses, employing wide-band frequency-modulated continuous wave…
Salient object detection (SOD) methods for 2D images have great significance in the field of human-computer interaction (HCI). However, as a common data format in HCI, the SOD research in the form of 3D point cloud data remains limited. Previous works commonly treat this task as point cloud segmenta…
Decision-making tasks have highlighted fundamental challenges in grounding decisions within real-world contexts. Traditional decision knowledge utilization methods often struggle to effectively integrate structured decision constraints, limiting their ability to decompose high-level tasks, maintain
Workflows play a crucial role in enhancing enterprise efficiency by orchestrating complex processes with multiple tools or components. However, hand-crafted workflow construction requires expert knowledge, presenting significant technical barriers. Recent advancements in Large Language Models (LLMs)…
Although there are commercial platforms with large antenna arrays operating over wide bands, narrow-band signals remain favored due to the hardware complexity and maximum unambiguous range considerations. This paper introduces a radio frequency (RF) imaging method employing multiple narrow-band freq…
Transformer has gained widespread adoption in modeling time series due to the exceptional ability of its self-attention mechanism in capturing long-range dependencies. However, when processing time series data with numerous variates, the vanilla self-attention mechanism tends to distribute attention…
Agile quadrotor flight relies on rapidly planning and accurately tracking time-optimal trajectories, a technology critical to their application in the wild. However, the computational burden of computing time-optimal trajectories based on the full quadrotor dynamics (typically on the order of minute
Functional near-infrared spectroscopy (fNIRS) promises a non-intrusive way to measure real-time brain activity and build responsive brain-computer interfaces. A primary barrier to realizing this technology's potential has been that observed fNIRS signals vary significantly across human users. Buildi…