38 citations · 72 across the 18 of their papers we have counts for
8 papers · 1 filter
Fairness-Aware Graph Representation Learning with Limited Demographic Information
Zichong Wang, Zhipeng Yin, Liping Yang +4
Ensuring fairness in Graph Neural Networks is fundamental to promoting trustworthy and socially responsible machine learning systems. In response, numerous fair graph learning meth…
AI Fairness Beyond Complete Demographics: Current Achievements and Future Directions
Zichong Wang, Zhipeng Yin, Roland H. C. Yap +1
Fairness in artificial intelligence (AI) has become a growing concern due to discriminatory outcomes in AI-based decision-making systems. While various methods have been proposed t…
Generative AI in Depth: A Survey of Recent Advances, Model Variants, and Real-World Applications
Shamim Yazdani, Akansha Singh, Nripsuta Saxena +6
In recent years, deep learning based generative models, particularly Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models (DMs), have been…
Towards Transparent AI: A Survey on Explainable Language Models
Avash Palikhe, Zichong Wang, Zhipeng Yin +4
Language Models (LMs) have significantly advanced natural language processing and enabled remarkable progress across diverse domains, yet their black-box nature raises critical con…
AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Models
Zhipeng Yin, Zichong Wang, Avash Palikhe +3
Generative models have achieved impressive results in text to image tasks, significantly advancing visual content creation. However, this progress comes at a cost, as such models r…
Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification
Jintao Qu, Zichong Wang, Chenhao Wu +1
Neural networks have achieved remarkable success in time series classification, but their reliance on large amounts of labeled data for training limits their applicability in cold-…
Towards Transparent AI: A Survey on Explainable Large Language Models
Avash Palikhe, Zhenyu Yu, Zichong Wang +1
Large Language Models (LLMs) have played a pivotal role in advancing Artificial Intelligence (AI). However, despite their achievements, LLMs often struggle to explain their decisio…
Datasets for Fairness in Language Models: An In-Depth Survey
Jiale Zhang, Zichong Wang, Avash Palikhe +2
Despite the growing reliance on fairness benchmarks to evaluate language models, the datasets that underpin these benchmarks remain critically underexamined. This survey addresses…