Search Query
Search query optimization is a broad field aiming to improve the efficiency and effectiveness of information retrieval across diverse applications, from game playing and code generation to scientific literature exploration and medical image analysis. Current research focuses on developing novel algorithms, such as adaptive Monte Carlo Tree Search and various transformer-based architectures, to enhance search strategies and reduce computational costs. These advancements have significant implications for various fields, improving the speed and accuracy of tasks ranging from AI decision-making to large-scale data analysis and medical diagnosis.
Papers
In Search of Verifiability: Explanations Rarely Enable Complementary Performance in AI-Advised Decision Making
Raymond Fok, Daniel S. Weld
Synergistic Interplay between Search and Large Language Models for Information Retrieval
Jiazhan Feng, Chongyang Tao, Xiubo Geng, Tao Shen, Can Xu, Guodong Long, Dongyan Zhao, Daxin Jiang