Cover Image

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wei, Zeming, Wang, Yifei, Li, Ang, Mo, Yichuan, Wang, Yisen
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computation and Language Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fight Back Against Jailbreaking via Prompt Adversarial Tuning
by: Mo, Yichuan, et al.
Published: (2024)

Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
by: Chen, Taiye, et al.
Published: (2025)

TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
by: Mo, Yichuan, et al.
Published: (2024)

Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
by: Zheng, Xiaosen, et al.
Published: (2024)

Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training
by: Wang, Yisen, et al.
Published: (2025)

Boosting Jailbreak Attack with Momentum
by: Zhang, Yihao, et al.
Published: (2024)

PID: Prompt-Independent Data Protection Against Latent Diffusion Models
by: Li, Ang, et al.
Published: (2024)

Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models
by: Li, Xiao, et al.
Published: (2024)

EnJa: Ensemble Jailbreak on Large Language Models
by: Zhang, Jiahao, et al.
Published: (2024)

Pruning for Protection: Increasing Jailbreak Resistance in Aligned LLMs Without Fine-Tuning
by: Hasan, Adib, et al.
Published: (2024)

Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
by: Rando, Javier, et al.
Published: (2024)

Rethinking How to Evaluate Language Model Jailbreak
by: Cai, Hongyu, et al.
Published: (2024)

Jailbreaking Large Language Models with Symbolic Mathematics
by: Bethany, Emet, et al.
Published: (2024)

ThinkGuard: Deliberative Slow Thinking Leads to Cautious Guardrails
by: Wen, Xiaofei, et al.
Published: (2025)

How to Craft Backdoors with Unlabeled Data Alone?
by: Wang, Yifei, et al.
Published: (2024)

MILE: A Mutation Testing Framework of In-Context Learning Systems
by: Wei, Zeming, et al.
Published: (2024)

CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models
by: Zhou, Guanghao, et al.
Published: (2025)

LLMs can be Dangerous Reasoners: Analyzing-based Jailbreak Attack on Large Language Models
by: Lin, Shi, et al.
Published: (2024)

TrinityGuard: A Unified Framework for Safeguarding Multi-Agent Systems
by: Wang, Kai, et al.
Published: (2026)

TurboFuzzLLM: Turbocharging Mutation-based Fuzzing for Effectively Jailbreaking Large Language Models in Practice
by: Goel, Aman, et al.
Published: (2025)

An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
by: Boreiko, Valentyn, et al.
Published: (2024)

A Mousetrap: Fooling Large Reasoning Models for Jailbreak with Chain of Iterative Chaos
by: Yao, Yang, et al.
Published: (2025)

Jailbreak Attacks and Defenses Against Large Language Models: A Survey
by: Yi, Sibo, et al.
Published: (2024)

Low-Resource Languages Jailbreak GPT-4
by: Yong, Zheng-Xin, et al.
Published: (2023)

Sparse Tokens Suffice: Jailbreaking Audio Language Models via Token-Aware Gradient Optimization
by: Fang, Zheng, et al.
Published: (2026)

Lifelong Safety Alignment for Language Models
by: Wang, Haoyu, et al.
Published: (2025)

Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive Scoring
by: Hua, Peichun, et al.
Published: (2025)

Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
by: Zhang, Yihao, et al.
Published: (2024)

Automata-Based Steering of Large Language Models for Diverse Structured Generation
by: Luan, Xiaokun, et al.
Published: (2025)

AutoAdv: Automated Adversarial Prompting for Multi-Turn Jailbreaking of Large Language Models
by: Reddy, Aashray, et al.
Published: (2025)

ForgeDAN: An Evolutionary Framework for Jailbreaking Aligned Large Language Models
by: Cheng, Siyang, et al.
Published: (2025)

Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection
by: Hu, Xulin, et al.
Published: (2026)

Identifying and Understanding Cross-Class Features in Adversarial Training
by: Wei, Zeming, et al.
Published: (2025)

In-Context Unlearning: Language Models as Few Shot Unlearners
by: Pawelczyk, Martin, et al.
Published: (2023)

Jailbreaking in the Haystack
by: Shah, Rishi Rajesh, et al.
Published: (2025)

JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs
by: Chu, Junjie, et al.
Published: (2024)

Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes
by: Hu, Xiaomeng, et al.
Published: (2024)

SequentialBreak: Large Language Models Can be Fooled by Embedding Jailbreak Prompts into Sequential Prompt Chains
by: Saiem, Bijoy Ahmed, et al.
Published: (2024)

MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks
by: Cornacchia, Giandomenico, et al.
Published: (2024)

Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
by: Fang, Zhicheng, et al.
Published: (2026)