NeurIPS 2024PastSafety & alignment
Red Teaming GenAI: What Can We Learn from Adversaries?
Red Teaming GenAI Workshop @ NeurIPS'24
- Submission deadline
- Sep 21, 2024, 21:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (38)
Fetched from OpenReview (v2) on 2026-06-10.
A Formal Framework for Assessing and Mitigating Emergent Security Risks in Generative AI Models: Bridging Theory and Dynamic Risk Mitigation
A Realistic Threat Model for Large Language Model Jailbreaks
Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models
Adversarial Negotiation Dynamics in Generative Language Models
Algorithmic Oversight for Deceptive Reasoning
Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs
An Adversarial Perspective on Machine Unlearning for AI Safety
Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI
Between the Bars: Gradient-based Jailbreaks are Bugs that induce Features
Code-Switching Red-Teaming: LLM Evaluation for Safety and Multilingual Understanding
CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation
Curiosity-driven Red teaming for Large Language Models
Decoding Biases: An Analysis of Automated Methods and Metrics for Gender Bias Detection in Language Models
Decompose, Recompose, and Conquer: Multi-modal LLMs are Vulnerable to Compositional Adversarial Attacks in Multi-Image Queries
Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning
Does Refusal Training in LLMs Generalize to the Past Tense?
Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage
iART - Imitation guided Automated Red Teaming
Infecting LLM Agents via Generalizable Adversarial Attack
Interactive Semantic Interventions for VLMs: Breaking VLMs with Human Ingenuity
Keep on Swimming: Real Attackers Only Need Partial Knowledge of a Multi-Model System
Large Language Model Detoxification: Data and Metric Solutions
Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning
Lessons From Red Teaming 100 Generative AI Products
LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
LLM-Assisted Red Teaming of Diffusion Models through "Failures Are Fated, But Can Be Faded"
MedAIScout: Automated Retrieval of Known Machine Learning Vulnerabilities in Medical Applications
Plentiful Jailbreaks with String Compositions
Rethinking LLM Memorization through the Lens of Adversarial Compression
SAGE-RT: Synthetic Alignment data Generation for Safety Evaluation and Red Teaming
Semantic Membership Inference Attack against Large Language Models
SkewAct: Red Teaming Large Language Models via Activation-Skewed Adversarial Prompt Optimization
Stability Evaluation of Large Language Models via Distributional Perturbation Analysis
Steganography in Large Language Models: Investigating Emergence and Mitigations
Text-Diffusion Red-Teaming of Large Language Models: Unveiling Harmful Behaviors with Proximity Constraints
TOFU: A Task of Fictitious Unlearning for LLMs
What Features in Prompts Jailbreak LLMs? Investigating the Mechanisms Behind Attacks