Large language models (LLMs) have attracted significant attention in recommendation
systems. Current LLM-based recommender systems primarily rely on supervised fine-tuning …

Detecting biases in the outputs produced by generative models is essential to reduce the
potential risks associated with their application in critical settings. However, the majority of …

Recent advances in Large Language Models (LLMs) have enabled human-like responses
across various tasks, raising questions about their ethical decision-making capabilities and …

Abstract Language models are trained on vast datasets sourced from the internet, which
inevitably contain biases that reflect societal norms, stereotypes, and political inclinations …