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20242026
most citedFairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications

38 citations · 43 across the 9 of their papers we have counts for

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cs.LG2026

FairLMs: A Turnkey Library for Fairness in Language Models

Jiale Zhang, Michael Larionov, Zichong Wang +2

Fairness research on language models involves measuring bias, applying mitigation methods, and examining the evidence on which an evaluation rests. Existing tools offer complementa…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2024★ 38 cited

FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications

Zhipeng Yin, Sribala Vidyadhari Chinta, Zichong Wang +2

The integration of AI in education holds immense potential for personalizing learning experiences and transforming instructional practices. However, AI systems can inadvertently en…

cs.LG2024★ 2 cited

Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AI

Archer Amon, Zhipeng Yin, Zichong Wang +2

Generative AI is becoming increasingly prevalent in creative fields, sparking urgent debates over how current copyright laws can keep pace with technological innovation. Recent con…