{
  "id": 19439215,
  "title": "TreeAgent: Structure-Aware Memory Agent for Processing Long Hierarchical Data",
  "url": "https://urgent.news/2026/11/10/treeagent-structure-aware-memory-agent-for-processing-long",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-10T11:33:05.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2611.13946v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Practical Web applications increasingly require agents to interpret long conversations or documents. For inputs exceeding the context windows of large language models (LLMs), memory agents process segments sequentially and retain past information in bounded memory. However, they typically divide inputs into flat token segments without preserving structure or hierarchy, causing three limitations…",
  "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."
}