{
  "id": 8148337,
  "title": "Cross-Modal Attention Acts as a Frequency Filter: Why Verbose Prompts Improve Robustness in Vision-Language Models",
  "url": "https://urgent.news/2026/09/17/cross-modal-attention-acts-as-a-frequency-filter-why-verbose-prompts",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-17T12:31:07.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.20139v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the question affects VLMs in two opposite ways. Verbose questions make VLMs substantially more robust---e.g., rephrasing \"Is there a cat?\" into \"Please look carefully and answer: is there a cat?\". Conversely, VLMs become more fragile under corruption when the question is semantically complex or…",
  "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."
}