MoE Pathfinder: Optimizing Mixture-of-Experts with Trajectory-Driven Pruning
Published:Dec 20, 2025 17:05
•1 min read
•ArXiv
Analysis
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.
Key Takeaways
- •Proposes a new pruning method for MoE models.
- •Utilizes trajectory-driven techniques for optimization.
- •Aims to improve performance and efficiency.
Reference
“The paper focuses on trajectory-driven expert pruning.”