Cover Image

VERA: Variational Inference Framework for Jailbreaking Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lochab, Anamika, Yan, Lu, Pynadath, Patrick, Zhang, Xiangyu, Zhang, Ruqi
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models
by: Liao, Qilin, et al.
Published: (2025)

Energy-Based Reward Models for Robust Language Model Alignment
by: Lochab, Anamika, et al.
Published: (2025)

Improved Techniques for Optimization-Based Jailbreaking on Large Language Models
by: Jia, Xiaojun, et al.
Published: (2024)

Jailbreak-Zero: A Path to Pareto Optimal Red Teaming for Large Language Models
by: Hu, Kai, et al.
Published: (2025)

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

RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking
by: Jiang, Yifan, et al.
Published: (2024)

JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models
by: Jin, Haibo, et al.
Published: (2024)

Uniform-Correct Policy Optimization: Breaking RLVR's Indifference to Diversity
by: Lochab, Anamika, et al.
Published: (2026)

Con Instruction: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalities
by: Geng, Jiahui, et al.
Published: (2025)

PrisonBreak: Jailbreaking Large Language Models with at Most Twenty-Five Targeted Bit-flips
by: Coalson, Zachary, et al.
Published: (2024)

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

User Inference Attacks on Large Language Models
by: Kandpal, Nikhil, et al.
Published: (2023)

Why Any-Order Autoregressive Models Need Two-Stream Attention: A Structural-Semantic Tradeoff
by: Pynadath, Patrick, et al.
Published: (2026)

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

Hijacking Large Language Models via Adversarial In-Context Learning
by: Zhou, Xiangyu, et al.
Published: (2023)

Controlled LLM Decoding via Discrete Auto-regressive Biasing
by: Pynadath, Patrick, et al.
Published: (2025)

Learning to Poison Large Language Models for Downstream Manipulation
by: Zhou, Xiangyu, et al.
Published: (2024)

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

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

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

Generative Frontiers: Why Evaluation Matters for Diffusion Language Models
by: Pynadath, Patrick, et al.
Published: (2026)

On the Effectiveness of Membership Inference in Targeted Data Extraction from Large Language Models
by: Sahili, Ali Al, et al.
Published: (2025)

SVIP: Towards Verifiable Inference of Open-source Large Language Models
by: Sun, Yifan, et al.
Published: (2024)

A StrongREJECT for Empty Jailbreaks
by: Souly, Alexandra, et al.
Published: (2024)

From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks
by: Zhang, Zhexin, et al.
Published: (2024)

Watermarking Language Models with Error Correcting Codes
by: Chao, Patrick, et al.
Published: (2024)

Jailbreaking Attack against Multimodal Large Language Model
by: Niu, Zhenxing, et al.
Published: (2024)

Privacy Preserving In-Context-Learning Framework for Large Language Models
by: Bhusal, Bishnu, et al.
Published: (2025)

Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models
by: Meeus, Matthieu, et al.
Published: (2023)

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

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

AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)

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

Prompt Public Large Language Models to Synthesize Data for Private On-device Applications
by: Wu, Shanshan, et al.
Published: (2024)

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

What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
by: Fan, Mingyuan, et al.
Published: (2026)

Composite Backdoor Attacks Against Large Language Models
by: Huang, Hai, et al.
Published: (2023)

Membership Inference Attacks and Privacy in Topic Modeling
by: Manzonelli, Nico, 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)

Adaptive Pre-training Data Detection for Large Language Models via Surprising Tokens
by: Zhang, Anqi, et al.
Published: (2024)