{
  "id": 4154,
  "url": "https://arxiv.org/abs/2605.17894v1",
  "title": "Evaluating Cognitive Age Alignment in Interactive AI Agents",
  "summary": "While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across domains ranging from daily life to advanced scientific research, a profound gap remains between artificial and human intelligence. Despite the integration of powerful tools and advanced MLLMs, state-of-the-art AI agents frequently fail at foundational, seemingly simple tasks that a child can resolve with ease. Inspired by the Wechsler Intelligence Sc",
  "authors": "Yifan Shen, Jiawen Zhang, Jian Xu, Junho Kim, Ismini Lourentzou, Xu Cao et al.",
  "category": "research",
  "topics": "safety-alignment,children-education,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-18T05:56:22.000Z",
  "fetched_at": "2026-07-14T16:30:45.941Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4154",
  "original_url": "https://arxiv.org/abs/2605.17894v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}