Zibin Zheng

Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation

Kefeng Duan, Dewu Zheng, Yanlin Wang, et al.

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

Kefeng Duan, Dewu Zheng, Yanlin Wang, et al.

SWE-Prime: Fewer Trajectories, Better Performance

Dewu Zheng, Ruizhe Ye, Yanlin Wang, et al.

From Static to Dynamic: Benchmarking Real-World Code Review with MCR-Bench

Dewu Zheng, Yanlin Wang, Xiwen Wang, et al.

DyMoE: Dynamic Expert Orchestration with Mixed-Precision Quantization for Efficient MoE Inference on Edge

Yuegui Huang, Zhiyuan Fang, Weiqi Luo, et al.

This paper presents DyMoE, a technique to make large AI models with multiple expert components run efficiently on edge devices (like mobile phones or IoT devices) by intelligently compressing less important experts while keeping critical ones intact. The method uses dynamic compression strategies that adapt based on which experts matter most and where in the model they're located, achieving 3-22x faster inference speeds compared to existing approaches while maintaining accuracy.