Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing
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performance across natural language tasks, yet they are trained on static corpora and their knowledge quickly becomes outdated in a fast-changing world.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 editors inject such a passage yet fail to use it: the edited model can recall the passage, but can neither answer atomic questions about its facts nor compose them into multi-hop reasoning. We attri...
| Authors | Tianci Liu, Zihan Dong, Tianchun Li et al. |
|---|---|
| Primary category | cs.CL |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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