arxiv
PublishedJuly 24, 2026 at 4:00 AM
—neutral
Incomplete Prompt Jailbreaks in Large Language Models
Publisher summary· verbatim
arXiv:2607.20473v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly released as open-weight models with safeguards against harmful requests. Nevertheless, sentence completion remains vulnerable to incomplete harmful prompts. In this work, we formalize this phenomenon as inc
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivBringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning5harxivSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks5harxivDistribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts5harxivIn RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning5hThe Bubble Brief
WEEKLYRead safety insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗