The paper contributes three reusable deployment patterns: hybrid RAG evidence construction, multi-channel retrieval and reranking produce auditable FAQ candidates, and trace-driven RAG and reranker improvement, where reranker fine-tuning is evaluated not only for in-domain gain but also for forgetting risk.
This work develops a four-part, intent-oriented taxonomy that organizes multi-turn jailbreaks by adversarial intent structure and finds that effectiveness is driven by how deliberately intent is organized across turns rather than by context length or query count.
Siyuan Li, Aodu Wulianghai, Zehao Liu et al.· 0 citations
This paper presents a proactive defense framework for securing LLMs against evolving multi-turn adversarial attacks that combines disruption, misdirection, and adaptation across successive interaction turns and employs a cooperative multi-agent architecture.
Si-Yuan Li, Zehao Liu, Hao-Yu Li et al.· 0 citations
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