{
  "id": 19506,
  "url": "https://arxiv.org/abs/2608.11660",
  "title": "Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing",
  "summary": "Large language models (LLMs) achieve remarkable performance across natural language tasks, yet they are trained on static corpora and their knowledge quickly becomes outdated in a fast-changing world. This motivates knowledge editing (KE), which updates specific knowledge in an LLM without changing unrelated others. Recent works move from structured knowledge triples toward unstructured KE (UKE), where the edit is a free-form passage that may state multiple facts at once. Nonetheless, existing e",
  "authors": "Tianci Liu, Zihan Dong, Tianchun Li, Yi-Chung Chen, Qiming Cao, Xingchen Wang",
  "category": "research",
  "topics": "regulation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T20:00:00.000Z",
  "fetched_at": "2026-08-15T05:10:17.122Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/19506",
  "original_url": "https://arxiv.org/abs/2608.11660",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}