AI Safety

Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings NeurIPS 2023 Trapdoor Normalization with Irreversible Ownership Verification ICML 2023 TrojanSQL: SQL Injection against Natural Language Interface to Database EMNLP 2023 TrojLLM: A Black-box Trojan Prompt Attack on Large Language Models NeurIPS 2023 UMD: Unsupervised Model Detection for X2X Backdoor Attacks ICML 2023 Understanding and Enhancing Robustness of Concept-Based Models AAAI 2023 Understanding and Mitigating Copying in Diffusion Models NeurIPS 2023 Understanding Backdoor Attacks through the Adaptability Hypothesis ICML 2023 Unified Adversarial Patch for Cross-Modal Attacks in the Physical World ICCV 2023 Unified Out-Of-Distribution Detection: A Model-Specific Perspective ICCV 2023 Uniformly Conservative Exploration in Reinforcement Learning AISTATS 2023 Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability ICML 2023 Unveiling Safety Vulnerabilities of Large Language Models EMNLP 2023 Unveiling the Implicit Toxicity in Large Language Models EMNLP 2023 User-Centric Democratization towards Social Value Aligned Medical AI Services IJCAI 2023 Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study EACL 2023 Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis ACL 2023 Walking a Tightrope – Evaluating Large Language Models in High-Risk Domains EMNLP 2023 Watermarking LLMs with Weight Quantization EMNLP 2023 WAT: Improve the Worst-Class Robustness in Adversarial Training AAAI 2023 When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization EACL 2023 Who Should Predict? Exact Algorithms For Learning to Defer to Humans AISTATS 2023 A Causal Analysis of Harm NeurIPS 2022 A Complete Criterion for Value of Information in Soluble Influence Diagrams AAAI 2022 ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation EMNLP 2022