MoE Pathfinder: Optimizing Mixture-of-Experts with Trajectory-Driven Pruning

This research introduces a novel pruning technique for Mixture-of-Experts (MoE) models, leveraging trajectory-driven methods to enhance efficiency. The paper's contribution lies in its potential to improve the performance and reduce the computational cost of large language models.