116 citations · 487 across the 22 of their papers we have counts for
22 papers
You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning
Tianmeng Yang, Jiahao Meng, Min Zhou +4
Recent research on the robustness of Graph Neural Networks (GNNs) under noises or attacks has attracted great attention due to its importance in real-world applications. Most previ…
Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning
Tianmeng Yang, Min Zhou, Yujing Wang +4
Graph Active Learning (GAL), which aims to find the most informative nodes in graphs for annotation to maximize the Graph Neural Networks (GNNs) performance, has attracted many res…
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders
Defu Cao, James Enouen, Yujing Wang +4
Causal analysis for time series data, in particular estimating individualized treatment effect (ITE), is a key task in many real-world applications, such as finance, retail, health…
Convolution-enhanced Evolving Attention Networks
Yujing Wang, Yaming Yang, Zhuo Li +7
Attention-based neural networks, such as Transformers, have become ubiquitous in numerous applications, including computer vision, natural language processing, and time-series anal…
Binary Classification with Positive Labeling Sources
Jieyu Zhang, Yujing Wang, Yaming Yang +2
To create a large amount of training labels for machine learning models effectively and efficiently, researchers have turned to Weak Supervision (WS), which uses programmatic label…
Stylized Knowledge-Grounded Dialogue Generation via Disentangled Template Rewriting
Qingfeng Sun, Can Xu, Huang Hu +6
Current Knowledge-Grounded Dialogue Generation (KDG) models specialize in producing rational and factual responses. However, to establish long-term relationships with users, the KD…