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Linguistic Loopholes in LLM Unlearning: From a 174-Language Benchmark to Coverage-Aware Unlearning
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Research reveals LLM unlearning in one language fails across others, exposing cross-lingual knowledge retention loopholes.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 1 October 2026
- Collected by OneBench
- 2 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2609.40286v1 Announce Type: new Abstract: Unlearning a fact in one language does not guarantee its removal in others as changing the query or even the…
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OneBench interpretation
Institutional assessment
So what
Cross-lingual retention of targeted unlearned data complicates privacy compliance and Right to be Forgotten enforcement in global models.
Do what
Review model unlearning and data deletion verification frameworks with the team responsible for model risk management.