For An Exciting Tomorrow
arXiv:2510.00919v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) with foundation models has achieved strong performance across diverse tasks, but their…
arXiv:2510.01914v1 Announce Type: cross Abstract: Since the defect detection of conventional industry components is time-consuming and labor-intensive, it leads to…
arXiv:2510.01910v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are widely adopted in Web-related applications, serving as a core technique…
arXiv:2510.00733v2 Announce Type: replace-cross Abstract: We introduce DeepFHT, a survival-analysis framework that couples deep neural networks with first hitting time…
arXiv:2510.00022v1 Announce Type: new Abstract: As autonomous systems move from prototypes to real deployments, the ability of multiple agents to…