{
  "id": 9068367,
  "title": "Artificial Structure Function Search: Preserving Artificial Functional Connectivity for Structured Pruning",
  "url": "https://urgent.news/2026/09/21/artificial-structure-function-search-preserving-artificial-functional",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-21T10:51:12.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.24401v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Structured pruning is a model compression technique that is used to reduce the computational cost of deploying deep neural networks on resource-constrained devices. Popular methods of pruning rely on opaque heuristics or weight-based criteria that give no indication as to the structural dependencies in the network. To address these limitations we present Artificial Structure Function Search…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}