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
Planning In Natural Language Improves LLM Search For Code Generation
Evan Wang, Federico Cassano, Catherine Wu, Yunfeng Bai, Will Song, Vaskar Nath, Ziwen Han, Sean Hendryx, Summer Yue, Hugh Zhang
In Search of Trees: Decision-Tree Policy Synthesis for Black-Box Systems via Search
Emir Demirović, Christian Schilling, Anna Lukina