{
  "id": 15902,
  "url": "https://arxiv.org/abs/2608.01742v1",
  "title": "MemSIF: From Structured Interactions to Dual-Track Fact Memory for LLM Agents",
  "summary": "Long-term memory is critical for LLM agents operating over long-horizon interactions. However, several persistent limitations of existing memory systems can be traced to two recurring misalignment patterns in long-term interaction settings: Temporal-Structural Misalignment (TSM) and Delayed Utility Manifestation (DUM). TSM arises when temporal proximity does not reliably align with topical or event-level relatedness, whereas DUM arises when write-time salience does not reliably predict future qu",
  "authors": "YuFei Luo, Xiucheng Xu, Zhen Yang",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-03T06:09:57.000Z",
  "fetched_at": "2026-08-04T05:10:21.797Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/15902",
  "original_url": "https://arxiv.org/abs/2608.01742v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}