{
  "id": 10846333,
  "title": "NeuronEye: Query-Guided Visual Concept Activation for Vision-Language Reasoning",
  "url": "https://urgent.news/2026/09/29/neuroneye-query-guided-visual-concept-activation-for-vision-language",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-29T17:44:09.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.38098v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Current vision-language models (VLMs) encode visual information in dense hidden states where object identity, spatial layout, and local attributes are implicitly entangled rather than explicitly disentangled, limiting their ability to isolate and modulate the specific visual evidence required by a given language query. Inspired by sparse population coding and top-down modulation in biological…",
  "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."
}