Xiang Zhang

Achieving state-of-the-art accuracy in knowledge distillation while maintaining a lightweight framework could redefine efficiency benchmarks in model training.

AGREE achieves superior clustering performance by effectively balancing attribute interaction and graph topology, overcoming the limitations of traditional methods.