{
  "id": 527028,
  "title": "Multimodal Model Diffing for Feature Discovery and Control",
  "url": "https://urgent.news/2026/08/10/multimodal-model-diffing-for-feature-discovery-and-control",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-10T17:59:30.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.09928v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to identify, audit, or control. While applicable to post-hoc inspection, hidden states that are decomposed into interpretable feature directions using sparse autoencoders (SAEs) neither readily isolate which features are changed by multimodal…",
  "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."
}