SOTAVerified

Red Teaming

Papers

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Showing 201–250 of 251 papers

TitleStatusHype
A Red Teaming Framework for Securing AI in Maritime Autonomous Systems—0
Seamless: Multilingual Expressive and Streaming Speech TranslationCode6
DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions—0
InfoPattern: Unveiling Information Propagation Patterns in Social MediaCode0
JAB: Joint Adversarial Prompting and Belief Augmentation—0
RLHFPoison: Reward Poisoning Attack for Reinforcement Learning with Human Feedback in Large Language Models—0
Stealthy and Persistent Unalignment on Large Language Models via Backdoor InjectionsCode0
Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework—0
Trojan Activation Attack: Red-Teaming Large Language Models using Activation Steering for Safety-AlignmentCode1
Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts—0
AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications—0
MART: Improving LLM Safety with Multi-round Automatic Red-Teaming—0
Summon a Demon and Bind it: A Grounded Theory of LLM Red Teaming—0
LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B—0
Language Model Unalignment: Parametric Red-Teaming to Expose Hidden Harms and BiasesCode1
Attack Prompt Generation for Red Teaming and Defending Large Language ModelsCode1
Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models—0
Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?Code1
Large Language Model UnlearningCode1
ASSERT: Automated Safety Scenario Red Teaming for Evaluating the Robustness of Large Language ModelsCode0
Catastrophic Jailbreak of Open-source LLMs via Exploiting GenerationCode1
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!Code2
Can Language Models be Instructed to Protect Personal Information?—0
Low-Resource Languages Jailbreak GPT-4—0
No Offense Taken: Eliciting Offensiveness from Language ModelsCode0
GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak PromptsCode2
Red Teaming Generative AI/NLP, the BB84 quantum cryptography protocol and the NIST-approved Quantum-Resistant Cryptographic Algorithms—0
Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic PromptsCode1
The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward—0
Red-Teaming Large Language Models using Chain of Utterances for Safety-AlignmentCode1
GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherCode2
FLIRT: Feedback Loop In-context Red Teaming—0
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language ModelsCode1
Model Card and Evaluations for Claude Models—0
Jailbroken: How Does LLM Safety Training Fail?Code1
Explore, Establish, Exploit: Red Teaming Language Models from ScratchCode1
Red Teaming Language Model Detectors with Language ModelsCode1
Seeing Seeds Beyond Weeds: Green Teaming Generative AI for Beneficial Uses—0
Query-Efficient Black-Box Red Teaming via Bayesian OptimizationCode1
Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback—0
Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity—0
Can Large Language Models Change User Preference Adversarially?—0
Red-Teaming the Stable Diffusion Safety Filter—0
Red Teaming with Mind Reading: White-Box Adversarial Policies Against RL AgentsCode0
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons LearnedCode3
CTI4AI: Threat Intelligence Generation and Sharing after Red Teaming AI Models—0
Red Teaming Language Models with Language ModelsCode1
Automating Privilege Escalation with Deep Reinforcement Learning—0
Computational Red Teaming in a Sudoku Solving Context: Neural Network Based Skill Representation and Acquisition—0
A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human to Autonomous Eliciting Agents—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SUDOAttack Success Rate41—Unverified