cs.NE · 2026-07-20 · No. 59

Neural and Evolutionary Computing, 2026-07-20.

2 new papers in cs.NE. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Evolutionary Algorithm-Guided LLMs for Physics-Informed Neural Network Design

    Xu Yang, Mingyang Yu, Jing Xu, Keqian Li

    cs.NE · cs.AI

    Physics-informed neural networks (PINNs) are unusually sensitive to interacting choices of architecture, activation, loss weighting, collocation, optimization, and constraint enforcement. Large language models (LLMs) can propose these choices, but independent recommendations do not accumulate experience from previously trained PINNs. We propose a closed-loop evolutionary algorithm that guides an LLM to generate complete, executable PINN...

    arxiv.org/abs/2607.15560 · PDF

  2. 02

    NeuronSoup: Evolving Asynchronous, Shared-Neuron Temporal Graphs without Backpropagation

    Subodh Kalia

    cs.NE · cs.LG

    We present NeuronSoup, a neural computation architecture that replaces synchronous layer-by-layer processing with asynchronous, delay-mediated signal propagation through a pool of shared neurons. Each path in the network routes a continuous-valued signal from one input neuron to one output neuron through a variable number of intermediate hidden neurons. Hidden neurons are physically shared across paths: when two paths pass through the same...

    arxiv.org/abs/2607.15217 · PDF

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