2 citations · 2 across the 5 of their papers we have counts for
5 papers
ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
Yilang Zhang, Xiaodong Yang, Yiwei Cai +1
As large language models (LLMs) continue to scale in size, the computational overhead has become a major bottleneck for task-specific fine-tuning. While low-rank adaptation (LoRA)…
SimAug: Enhancing Recommendation with Pretrained Language Models for Dense and Balanced Data Augmentation
Yuying Zhao, Xiaodong Yang, Huiyuan Chen +4
Deep Neural Networks (DNNs) are extensively used in collaborative filtering due to their impressive effectiveness. These systems depend on interaction data to learn user and item e…
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Song Wang, Xiaodong Yang, Rashidul Islam +4
To deal with distribution shifts in graph data, various graph out-of-distribution (OOD) generalization techniques have been recently proposed. These methods often employ a two-step…
GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization
Xiaodong Yang, Xiaoting Li, Huiyuan Chen +1
Recent studies show that well-devised perturbations on graph structures or node features can mislead trained Graph Neural Network (GNN) models. However, these methods often overloo…
SimCE: Simplifying Cross-Entropy Loss for Collaborative Filtering
Xiaodong Yang, Huiyuan Chen, Yuchen Yan +5
The learning objective is integral to collaborative filtering systems, where the Bayesian Personalized Ranking (BPR) loss is widely used for learning informative backbones. However…