Abstract: The performance of traditional multiobj ective evolutionary algorithms (MOEAs) often deteriorates rapidly when using them to solve large-scale multiobjective optimization problems (LMOPs).

Recently, graph convolutional network (GCN)-based models, e.g., GraphSAGE, have drawn a lot of attention for their success in inductive NRL. When conducting unsupervised learning on large-scale graphs ...

WebThinker is a deep research framework fully powered by large reasoning models (LRMs). WebThinker enables LRMs to autonomously search, deeply explore web pages, and draft research reports, all within ...