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cs.MA2026
Width, Memory, and Delay: A Resource Accounting for the Limits of Flat Multi-Agent Systems
Oleksandr Kuznetsov, Emanuele Frontoni
A recurring question in the design of scalable multi-agent systems -- from robot swarms to collectives of large-language-model (LLM) agents -- is whether adding more agents can, on…
cs.CV2026
Structural Kolmogorov-Arnold Convolutions: Learnable Function on the Values or the Filter Shape as Parameter-Efficient Alternative to Per-Edge Convolutional KANs
Stefano Mereu, Oleksandr Kuznetsov, Gabriele Marchello +4
Convolutional Kolmogorov--Arnold Networks (KANs) replace the fixed weights of a convolutional kernel with learnable univariate functions. The dominant formulation attaches one such…