harmful content

Large Language Model Unlearning NeurIPS 2024 Making Harmful Behaviors Unlearnable for Large Language Models ACL 2024 MLLM-Protector: Ensuring MLLM’s Safety without Hurting Performance EMNLP 2024 Overthinking the Truth: Understanding how Language Models Process False Demonstrations ICLR 2024 Red Teaming Visual Language Models ACL 2024 Representation Noising: A Defence Mechanism Against Harmful Finetuning NeurIPS 2024 SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding ACL 2024 Safety Arithmetic: A Framework for Test-time Safety Alignment of Language Models by Steering Parameters and Activations EMNLP 2024 Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models ICML 2024 Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions ICLR 2024 Sandwich attack: Multi-language Mixture Adaptive Attack on LLMs NAACL 2024 Towards Safer Large Language Models through Machine Unlearning ACL 2024 Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis EMNLP 2024 ToxiCraft: A Novel Framework for Synthetic Generation of Harmful Information EMNLP 2024 UNIWIZ: A Unified Large Language Model Orchestrated Wizard for Safe Knowledge Grounded Conversations ACL 2024 Unlearning Traces the Influential Training Data of Language Models ACL 2024 Who's asking? User personas and the mechanics of latent misalignment NeurIPS 2024 Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systems EMNLP 2023 Multi-step Jailbreaking Privacy Attacks on ChatGPT EMNLP 2023 Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models NeurIPS 2022 Detecting and Understanding Harmful Memes: A Survey IJCAI 2022 Measuring Harmful Representations in Scandinavian Language Models EMNLP 2022 Red Teaming Language Models with Language Models EMNLP 2022