Author

Jinghang Huang

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#artificial intelligence Preprint Sep 2026

DEALS: Decentralized Expertise-Aware Load Serving for Multi-Agent LLM Systems

Experiments show that DEALS not only improves performance along multiple dimensions (e.g., answer accuracy and task throughput) in both homogeneous and heterogeneous agent pools, but also balances agent expertise and workload in a self-organized manner, enabling effective decentralized coordination.

Jing-Hang Huang, Wen-Bin Wang, Yan-Chuan Yin et al. · 0 citations

Preprint Aug 2026

Parallelizable Gradient-Based Optimization For Multi-Objective MaxCut

This paper develops a differentiable framework for multi-objective MaxCut by combining an adjacency-based quadratic formulation with linear scalarization, thereby reducing the problem to a preference-conditioned single-objective signed-weight MaxCut problem.

Jing-Hang Huang, Cheng-Han Huang, Alvaro Velasquez et al. · 0 citations