Author

Jian Wan

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Review Open access Sep 2026

Towards Optimal Speculative Decoding: A Comprehensive Survey on Optimizations and Future Directions

How draft effectiveness, verification efficiency, and system execution jointly determine end-to-end performance is examined, and the trade-offs underlying existing optimization directions are critically synthesized.

Yu-Yang Ji, Wenjian Xu, Xiao-Hong Qian et al. · ACM Computing Surveys · 0 citations

#machine learning Preprint Aug 2026

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing

This work presents Task-to-Model Optimization (T2MO), a data-driven methodology for optimizing model selection in production coding workflows, and describes the methodology, optimization objective, evaluation protocol, and governance loop in a form suitable for production deployment and future empirical study.

Srinivasan Manoharan, Junhua Zhao, Fang Tu et al. · 0 citations

Open access Jul 2026

One-Shot Federated Learning With Lightweight Intermediate Models in Wireless Sensor Network Setting

Experimental results on three datasets demonstrate that FedLIM achieves superior global model accuracy compared to existing one-shot FL methods, particularly in highly heterogeneous environments.

Yexin Dou, Haijiang Wang, Jian Wan et al. · IEEE Internet of Things Jour... · 0 citations