{
  "id": 9256648,
  "title": "SpeakerMem-R1: Speaker-Centered Dual-Track Memory for Multi-Party Dialogue",
  "url": "https://urgent.news/2026/09/22/speakermem-r1-speaker-centered-dual-track-memory-for-multi-party",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-22T17:56:12.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.26780v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish who said what, whom each statement concerns, how individuals perceive one another, what information is shared by the group, and how states change over time. Recent studies on multi-party dialogue benchmarks show that existing general-purpose LLM…",
  "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."
}