{
  "id": 6536803,
  "title": "ConvMem: Convolutional Memory for Long-Context Reasoning",
  "url": "https://urgent.news/2026/09/09/convmem-convolutional-memory-for-long-context-reasoning",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-09T16:53:02.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.10441v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "While Large Language Models (LLMs) have demonstrated impressive capabilities, they often struggle with extremely long contexts due to fixed context limits. To address this, sequential approaches like MemAgent extend the effective context by reading text in segments and iteratively updating a fixed-size memory. However, this sequential paradigm suffers from high latency and requires costly…",
  "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."
}