{
  "id": 16834707,
  "title": "VideoLVR: Latent Visual Reasoning over Grounded Video Evidence",
  "url": "https://urgent.news/2026/10/27/videolvr-latent-visual-reasoning-over-grounded-video-evidence",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-27T17:41:56.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.37613v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Chain-of-thought reasoning has substantially advanced video understanding in multimodal large language models (MLLMs). However, language-based reasoning traces do not provide a reliable mechanism for models to revisit relevant visual evidence, leading to visual forgetting and impairing their ability to reason over video content. Existing approaches maintain visual grounding during reasoning in…",
  "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."
}