{
  "id": 5507,
  "url": "https://arxiv.org/abs/2604.20300v2",
  "title": "FSFM: A Biologically-Inspired Framework for Selective Forgetting of Agent Memory",
  "summary": "For LLM agents, memory management critically impacts efficiency, quality, and security. While much research focuses on retention, selective forgetting--inspired by human cognitive processes (hippocampal indexing/consolidation theory and Ebbinghaus forgetting curve)--remains underexplored. We argue that in resource-constrained environments, a well-designed forgetting mechanism is as crucial as remembering, delivering benefits across three dimensions: (1) efficiency via intelligent memory pruning,",
  "authors": "Yingjie Gu, Wenjian Xiong, Liqiang Wang, Pengcheng Ren, Chao Li, Xiaojing Zhang et al.",
  "category": "research",
  "topics": "agents-autonomy,environment,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-22T07:55:22.000Z",
  "fetched_at": "2026-07-14T16:31:48.874Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5507",
  "original_url": "https://arxiv.org/abs/2604.20300v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}