While" instruction-tuned" generative large language models (LLMs) have demonstrated an
impressive ability to generalize to new tasks, the training phases heavily rely on large …

Generating long-range skeleton-based human actions has been a challenging problem
since small deviations of one frame can cause a malformed action sequence. Most existing …

Bayesian neural networks (BNNs) offer uncertainty quantification but come with the
downside of substantially increased training and inference costs. Sparse BNNs have been …

In spatial crowdsourcing, both workers and tasks are added to the system on the fly, making
it a real-time platform with complex circumstances. Most research has focused on optimizing …

When virtual agents interact with humans, gestures are crucial to delivering their intentions
with speech. Previous multimodal co-speech gesture generation models required encoded …

In this paper, a deep learning-based model for 3D human motion generation from the text is
proposed via gesture action classification and an autoregressive model. The model focuses …

The present article presents a model of temporal prediction of the evolution of the number of
confirmed cases of the new coronavirus (SARS-CoV-2) in Brazil. This model is based on the …