2 papers
cs.DC2025
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism
Sandeep Polisetty, Juelin Liu, Kobi Falus +4
Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their superior performance in various graph analytical tasks. Mini…
cs.LG2025
Attacking All Tasks at Once Using Adversarial Examples in Multi-Task Learning
Lijun Zhang, Xiao Liu, Kaleel Mahmood +2
Visual content understanding frequently relies on multi-task models to extract robust representations of a single visual input for multiple downstream tasks. However, in comparison…