Addressing Bias and Unfairness in Information Retrieval Systems with Large Language Models: Challenges and Mitigation Strategies

Bias and unfairness are emerging as critical challenges in information retrieval (IR) systems that integrate large language models (LLMs), threatening the reliability and trustworthiness of these systems. This survey provides a unified perspective on these issues as distribution mismatch problems and systematically reviews the causes and mitigation strategies across different stages of LLM integration into IR.