Cover Image

Forbidden Facts: An Investigation of Competing Objectives in Llama-2

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Tony T., Wang, Miles, Hariharan, Kaivalya, Shavit, Nir
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

Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach
by: Wang, Tony T., et al.
Published: (2024)

Badllama 3: removing safety finetuning from Llama 3 in minutes
by: Volkov, Dmitrii
Published: (2024)

AdvPrefix: An Objective for Nuanced LLM Jailbreaks
by: Zhu, Sicheng, et al.
Published: (2024)

Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
by: Halawi, Danny, et al.
Published: (2024)

Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
by: Xu, Xiaoyu, et al.
Published: (2025)

IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs
by: Guo, Chuan, et al.
Published: (2026)

Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
by: Chu, Junjie, et al.
Published: (2024)

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

BlackDAN: A Black-Box Multi-Objective Approach for Effective and Contextual Jailbreaking of Large Language Models
by: Wang, Xinyuan, et al.
Published: (2024)

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
by: Wei, Zeming, et al.
Published: (2023)

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

The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs
by: Chen, Bocheng, et al.
Published: (2024)

Extracting Training Data from Diffusion Language Models via Infilling
by: Wang, Yihan, et al.
Published: (2026)

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

Probing the Robustness of Large Language Models Safety to Latent Perturbations
by: Gu, Tianle, et al.
Published: (2025)

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

When Thinking LLMs Lie: Unveiling the Strategic Deception in Representations of Reasoning Models
by: Wang, Kai, et al.
Published: (2025)

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

HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection
by: Wang, Yuxin, et al.
Published: (2024)

Directional Embedding Smoothing for Robust Vision Language Models
by: Wang, Ye, et al.
Published: (2026)

From Shortcuts to Triggers: Backdoor Defense with Denoised PoE
by: Liu, Qin, et al.
Published: (2023)

BadAgent: Inserting and Activating Backdoor Attacks in LLM Agents
by: Wang, Yifei, et al.
Published: (2024)

Federated In-Context LLM Agent Learning
by: Wu, Panlong, et al.
Published: (2024)

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

The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
by: Chen, Xiaoyi, et al.
Published: (2023)

Do Phone-Use Agents Respect Your Privacy?
by: Tang, Zhengyang, et al.
Published: (2026)

PIArena: A Platform for Prompt Injection Evaluation
by: Geng, Runpeng, et al.
Published: (2026)

MEUV: Achieving Fine-Grained Capability Activation in Large Language Models via Mutually Exclusive Unlock Vectors
by: Tong, Xin, et al.
Published: (2025)

Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models
by: Xu, Jiashu, et al.
Published: (2023)

Detecting Training Data of Large Language Models via Expectation Maximization
by: Kim, Gyuwan, et al.
Published: (2024)

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

An In-Depth Investigation of Data Collection in LLM App Ecosystems
by: Wu, Yuhao, et al.
Published: (2024)

Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
by: Lu, Ning, et al.
Published: (2023)

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

Textual Unlearning Gives a False Sense of Unlearning
by: Du, Jiacheng, et al.
Published: (2024)

PISanitizer: Preventing Prompt Injection to Long-Context LLMs via Prompt Sanitization
by: Geng, Runpeng, et al.
Published: (2025)

Machine Unlearning of Pre-trained Large Language Models
by: Yao, Jin, et al.
Published: (2024)

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

Instructional Fingerprinting of Large Language Models
by: Xu, Jiashu, et al.
Published: (2024)

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
by: Wang, Kun, et al.
Published: (2025)