cs.NE · 2026-07-04 · No. 43

Neural and Evolutionary Computing, 2026-07-04.

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

    Dendritic In-Context Learning in a Single-Layer Spiking Neural Network

    Juwei Shen, Yujie Wu, Changwen Chen

    cs.NE · cs.LG

    In-context learning (ICL) operates via implicit gradient descent embedded in the forward pass of modern AI architectures -- Transformers, Mamba, state-space models, and MLPs. Capturing this capability in biologically plausible Spiking Neural Networks (SNNs) has remained an open challenge: existing SNNs fail the Garg-2022 benchmark at non-trivial task dimensions. We trace this failure to a structural assumption: prior SNN designs route...

    arxiv.org/abs/2607.02283 · PDF

  2. 02

    Evolutionary Wave Function Collapse

    Dipika Rajesh, Ahmed Khalifa, Julian Togelius

    cs.NE · cs.AI

    Wave Function Collapse (WFC) is a widely used procedural content generation method that learns local adjacency constraints from example inputs to generate larger outputs. In this paper, we explore combining WFC with evolutionary search by evolving the small input examples used by WFC rather than directly evolving complete levels. In this approach, WFC acts as a genotype-to-phenotype mapping. The generated levels are then evaluated through...

    arxiv.org/abs/2607.02082 · PDF

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