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About this paper
Jiamu Zhang, Lingxi Zhang, Pengjun Lu, Qiyue Zhang, Yu-Neng Chuang, Zhengchen Li, Shuai Xu, Vipin Chaudhary and 1 more
The authors evaluate whether five methods can make multi-agent systems cheaper by restructuring them under a controlled benchmark. They hold starting systems and execution fixed, and compare each method with random pruning at the same edge budget. In the 20-cell main grid, optimized methods averaged −0.77 accuracy points versus −0.44 for random pruning; only DAGP beat its random control on average.
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