4 papers
SPA++: Generalized Graph Spectral Alignment for Versatile Domain Adaptation
Zhiqing Xiao, Haobo Wang, Xu Lu +3
Domain Adaptation (DA) aims to transfer knowledge from a labeled source domain to an unlabeled or sparsely labeled target domain under domain shifts. Most prior works focus on capt…
Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments
Deliang Jin, Gang Chen, Shuo Feng +2
Deep neural networks (DNNs) have achieved remarkable success across diverse domains, but their performance can be severely degraded by noisy or corrupted training data. Conventiona…
HMI: Hierarchical Knowledge Management for Efficient Multi-Tenant Inference in Pretrained Language Models
Jun Zhang, Jue Wang, Huan Li +6
The significant computational demands of pretrained language models (PLMs), which often require dedicated hardware, present a substantial challenge in serving them efficiently, esp…
MoNTA: Accelerating Mixture-of-Experts Training with Network-Traffc-Aware Parallel Optimization
Jingming Guo, Yan Liu, Yu Meng +4
The Mixture of Experts (MoE) is an advanced model architecture in the industry that combines multiple specialized expert models from various domains into a single supermodel. This…