Exhibitor Talk - NEC

This talk provides an overview of our papers featured at this conference, focusing on two complementary approaches to enhancing large language model (LLM) capabilities: internal reasoning enhancement and external tool integration. We investigate strategies to boost the intrinsic reasoning abilities of LLMs through advanced search algorithms and problem decomposition, specifically applied to automated code generation. Simultaneously, we explore how LLMs can enhance their problem-solving capacities by interacting with specialized external tools, including satisfiability solvers, optimization solvers, computer vision tools, and time series analysis tools. By integrating these internal and external enhancements, we aim to unlock new frontiers in artificial intelligence, enabling more sophisticated decision-making and problem-solving capabilities.