These Mathematicians Are Putting A.I. to the Test

Large language models struggle to solve research-level math questions. It takes a human to assess just how poorly they ...
EurekAlert!

Achieving >97% on GSM8K: Deeply understanding the problems makes LLMs better solvers for math word problems

Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks.
IEEE

Leveraging Transfer Learning in Deep Reinforcement Learning for Solving Combinatorial Optimization Problems Under Uncertainty

Abstract: In recent years, addressing the inherent uncertainties within Combinatorial Optimization Problems (COPs) reveals the limitations of traditional optimization methods. Although these methods ...
IEEE

Learning-Driven Algorithm With Dual Evolution Patterns for Solving Large-Scale Multiobjective Optimization Problems

Abstract: Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). Among them, ...