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References (13)

[1]
Knowledge-Driven Multi-Turn Jailbreaking on Large Language Models
2026Songze Li, Ruishi He et al.
[2]
Defense Against Indirect Prompt Injection via Tool Result Parsing
2026Qiang Yu, Xinran Cheng et al.
[3]
Recursive Language Models
2025Alex L. Zhang, Tim Kraska et al.
[4]
Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs
2025Giulio Zizzo, Giandomenico Cornacchia et al.
[5]
UniGuardian: A Unified Defense for Detecting Prompt Injection, Backdoor Attacks and Adversarial Attacks in Large Language Models
2025Huawei Lin, Yingjie Lao et al.
[6]
JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation
2025Shenyi Zhang, Yuchen Zhai et al.
[7]
Attention Tracker: Detecting Prompt Injection Attacks in LLMs
2024Kuo-Han Hung, Ching-Yun Ko et al.
[8]
SecAlign: Defending Against Prompt Injection with Preference Optimization
2024Sizhe Chen, Arman Zharmagambetov et al.
[9]
InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents
2024Qiusi Zhan, Zhixiang Liang et al.
[10]
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
2024Mantas Mazeika, Long Phan et al.
[11]
A Wolf in Sheep’s Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily
2023Peng Ding, Jun Kuang et al.
[12]
AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models
2023Xiaogeng Liu, Nan Xu et al.
[13]
Prompt Injection attack against LLM-integrated Applications
2023Yi Liu, Gelei Deng et al.

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"Developing a robust framework for detecting jailbreak attacks on language models using Recursive Language Models."

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