Lu Cheng

A new framework tackles fairness challenges in machine learning with limited data samples.

A new model improves stance detection using counterfactual data and contrastive learning.

Examining how fairness in machine learning can evolve across decisions and time.

Examining the challenges and methods of achieving fairness in machine learning.

Research explores language models’ ability to analyze social media interactions and tackle bullying.

Exploring how AI can assess language quality and the challenges involved.

Examining the challenges and biases of LLMs in healthcare applications.