Autonomous vehicles (AVs) have the potential to significantly revolutionize society by
providing a secure and efficient mode of transportation. Recent years have witnessed …

Obtaining accurate and diverse human motion prediction is essential to many industrial
applications, especially robotics and autonomous driving. Recent research has explored …

Contemporary attention-based sequential recommendations often encounter the
oversmoothing problem, which generates indistinguishable representations. Although …

Deep learning has recently achieved significant progress in trajectory forecasting. However,
the scarcity of trajectory data inhibits the data-hungry deep-learning models from learning …

Motion forecasting in highly interactive scenarios is a challenging problem in autonomous
driving. In such scenarios, we need to accurately predict the joint behavior of interacting …

Conditional behavior prediction (CBP) builds up the foundation for a coherent interactive
prediction and plan-ning framework that can enable more efficient and less conser-vative …

In recent years, the pervasive deployment and progression of autonomous driving
technology have engendered heightened demands, particularly within the intricate campus …

The detection of fake news has emerged as a pressing issue in the era of online social
media. To detect meticulously fabricated fake news, propagation paths are introduced to …

The design of a safe and reliable Autonomous Driving stack (ADS) is one of the most
challenging tasks of our era. These ADS are expected to be driven in highly dynamic …

Abstract Neural Topic Modeling has attracted significant attention from the Natural
Language Processing community due to its black-box inference property and has made …