Information Access

Information access research focuses on improving how individuals and systems retrieve and utilize data, encompassing diverse applications from legal question answering to scientific data analysis. Current research emphasizes developing efficient and equitable access methods, exploring techniques like federated learning to protect privacy while enabling collaborative model training, and employing reinforcement learning for dynamic resource allocation. These advancements are crucial for addressing challenges in various fields, including AI auditing, biomedical information retrieval, and ensuring fair access to powerful technologies like large language models.