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- Southeast UniversityCN5 papers
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cs.NE2026
A Scalable Benchmark Test Suite for Dynamic Multi-Objective Optimization with a Changing Number of Objectives
Ke Shang, Zhiyun Xiao, Yuxuan Liu +3
Dynamic multi-objective optimization with a changing number of objectives has recently attracted increasing attention due to its relevance to real-world problems whose evaluation c…
cs.DC2026
LAER-MoE: Load-Adaptive Expert Re-layout for Efficient Mixture-of-Experts Training
Xinyi Liu, Yujie Wang, Fangcheng Fu +4
Expert parallelism is vital for effectively training Mixture-of-Experts (MoE) models, enabling different devices to host distinct experts, with each device processing different inp…