Tunazzina Islam

Fairness in personalized text generation is not a one-size-fits-all solution—different strategies yield trade-offs across demographic disparities and personalization fidelity.

LLMs can act as effective "semantic judges" to refine and validate unsupervised text clusters, significantly improving coherence and interpretability without relying on labeled data.