NeurIPS 2024PastSafety & alignmentGenerative models
Neurips Safe Generative AI Workshop 2024
SafeGenAi
- Submission deadline
- Oct 5, 2024, 08:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (171)
Fetched from OpenReview (v2) on 2026-06-10.
$\textit{Who Speaks Matters}$: Analysing the Influence of the Speaker’s Ethnicity on Hate Classification
A Closer Look at System Message Robustness
A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
A Probabilistic Generative Method for Safe Physical System Control Problems
A Three-Branch Checks-and-Balances Framework for Context-Aware Ethical Alignment of Large Language Models
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI
AdvBDGen: Adversarially Fortified Prompt-Specific Fuzzy Backdoor Generator Against LLM Alignment
Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
AEGIS2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails
AI Red Teaming through the Lens of Measurement Theory
An Examination of AI-Generated Text Detectors Across Multiple Domains and Models
An Undetectable Watermark for Generative Image Models
Anchored Optimization and Contrastive Revisions: Addressing Reward Hacking in Alignment
AnyPrefer: An Automatic Framework for Preference Data Synthesis
Applying Refusal-Vector Ablation to Llama 3.1 70B Agents
Applying Sparse Autoencoders to Unlearn Knowledge in Language Models
Auditing Empirical Privacy Protection of Private LLM Adaptations
Auto-Enhance: Towards a Meta-Benchmark to Evaluate AI Agents' Ability to Improve Other Agents
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
Buffer Overflow in Mixture of Experts
Can Editing LLMs Inject Harm?
Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
Can Knowledge Editing Really Correct Hallucinations?
Can LLMs Verify Arabic Claims? Evaluating the Arabic Fact-Checking Abilities of Multilingual LLMs
Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity
ChatBug: A Common Vulnerability of Aligned LLMs Induced by Chat Templates
Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates
Choose Your Anchor Wisely: Effective Unlearning Diffusion Models via Concept Reconditioning
CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept
Concept Denoising Score Matching for Responsible Text-to-Image Generation
Concept Unlearning for Large Language Models
Controllable Generation via Locally Constrained Resampling
CoS: Enhancing Personalization and Mitigating Bias with Context Steering
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Cream: Consistency Regularized Self-Rewarding Language Models
Datasets for Navigating Sensitive Topics in Peference Data and Recommendations
Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations
Decoding Diffusion: A Scalable Framework for Unsupervised Analysis of Latent Space Biases and Representations Using Natural Language Prompts
DeepInception: Hypnotize Large Language Model to Be Jailbreaker
Designing Physical-World Universal Attacks on Vision Transformers
Detecting Origin Attribution for Text-to-Image Diffusion Models in RGB and Beyond
Differential Privacy of Cross-Attention with Provable Guarantee
Differentially Private Attention Computation
Differentially Private Sequential Data Synthesis with Structured State Space Models and Diffusion Models
DiffTextPure: Defending Large Language Models with Diffusion Purifiers
Do LLMs estimate uncertainty well in instruction-following?
Does Refusal Training in LLMs Generalize to the Past Tense?
Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Dynamic Negative Guidance of Diffusion Models: Towards Immediate Content Removal
EchoQA: A Large Collection of Instruction Tuning Data for Echocardiogram Reports
Efficient and Effective Uncertainty Quantification for LLMs
Efficiently Identifying Watermarked Segments in Mixed-Source Texts
Energy-Based Conceptual Diffusion Model
EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM?
Epistemic Integrity in Large Language Models
Exploring Memorization and Copyright Violation in Frontier LLMs: A Study of the New York Times v. OpenAI 2023 Lawsuit
Extracting Unlearned Information from LLMs with Activation Steering
Fair Image Generation from Pre-trained Models by Probabilistic Modeling
Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy
Gaussian Splatting Under Attack: Investigating Adversarial Noise in 3D Objects
GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence
GRE Score: Generative Risk Evaluation for Large Language Models
GuardFormer: Guardrail Instruction Pretraining for Efficient SafeGuarding
H-Space Sparse Autoencoders
Hallucination Detox: Sensitive Neuron Dropout (SeND) for Large Language Model Training
HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment
Has My System Prompt Been Used? Large Language Model Prompt Membership Inference
HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection
Hidden in Plain Text: Emergence & Mitigation of Steganographic Collusion in LLMs
Hidden in the Noise: Two-Stage Robust Watermarking for Images
Honesty to Subterfuge: In-Context Reinforcement Learning Can Make Honest Models Reward Hack
How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompt
How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold
How new data pollutes LLM knowledge and how to dilute it
How to Determine the Preferred Image Distribution of a Black-Box Vision-Language Model?
HyperFace: Generating Synthetic Face Recognition Datasets by Exploring Face Embedding Hypersphere
Identifying and Addressing Delusions for Target-Directed Decision Making
Imitation guided Automated Red Teaming
Improving LLM Group Fairness on Tabular Data via In-Context Learning
IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization
Inference, Fast and Slow: Reinterpreting VAEs for OOD Detection
Insights on Disagreement Patterns in Multimodal Safety Perception across Diverse Rater Groups
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
Integrating Object Detection Modality into Visual Language Model for Enhanced Autonomous Driving Agent
Interactive Semantic Interventions for VLMs: A Human-in-the-Loop Investigation of VLM Failure
INTERPRETABILITY OF LLM DECEPTION: UNIVERSAL MOTIF
INVESTIGATING ANNOTATOR BIAS IN LARGE LANGUAGE MODELS FOR HATE SPEECH DETECTION
Investigating Implicit Bias in Large Language Models: A Large-Scale Study of Over 50 LLMs
Investigating LLM Memorization: Bridging Trojan Detection and Training Data Extraction
Is What You Ask For What You Get? Investigating Concept Associations in Text-to-Image Models
Is Your Paper Being Reviewed by an LLM? Investigating AI Text Detectability in Peer Review
Jogging the Memory of Unlearned LLMs Through Targeted Relearning Attacks
Just rephrase it! Uncertainty estimation in closed-source language models via multiple rephrased queries
Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
Keep on Swimming: Real Attackers Only Need Partial Knowledge of a Multi-Model System
Language Models Can Articulate Their Implicit Goals
Large Language Model Benchmarks Do Not Test Reliability
Lexically-constrained automated prompt augmentation: A case study using adversarial T2I data
LLM Improvement for Jailbreak Defense: Analysis Through the Lens of Over-Refusal
LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
LoReUn: Data Itself Implicitly Provides Cues to Improve Machine Unlearning
Measuring Steerability in Large Language Models
MED: Exploring LLM Memorization of Encrypted Data
Memorization Detection Benchmark for Generative Image models
miniCodeProps: a Minimal Benchmark for Proving Code Properties
Mitigating Hallucinations in LVLMs via Summary-Guided Decoding
Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
Mix Data or Merge Models? Optimizing for Performance and Safety in Multilingual Contexts
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
MMLU-Pro+: Evaluating Higher-Order Reasoning and Shortcut Learning in LLMs
Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicity
Model Manipulation Attacks Enable More Rigorous Evaluations of LLM Capabilities
Model Pairing Using Embedding Translation for Backdoor Attack Detection on Open-Set Classification Tasks
MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning
MultiVerse: Exposing Large Language Model Alignment Problems in Diverse Worlds
Network Inversion for Training-Like Data Reconstruction
NMT-Obfuscator Attack: Ignore a sentence in translation with only one word
On a Spurious Interaction between Uncertainty Scores and Answer Evaluation Metrics in Generative QA Tasks
On Calibration of LLM-based Guard Models for Reliable Content Moderation
Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs
PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models
PopAlign: Population-Level Alignment for Fair Text-to-Image Generation
Pre-Training Multimodal Hallucination Detectors with Corrupted Grounding Data
Preserving Safety in Fine-Tuned Large Language Models: A Systematic Evaluation and Mitigation Strategy
Privacy Protection in Personalized Diffusion Models via Targeted Cross-Attention Adversarial Attack
Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
Pruning for Robust Concept Erasing in Diffusion Models
Red Teaming Language-Conditioned Robot Models via Vision Language Models
Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models
Representation Collapsing Problems in Vector Quantization
Retention Score: Quantifying Jailbreak Risks for Vision Language Models
Rethinking Adversarial Attacks as Protection Against Diffusion-based Mimicry
RLHS: Mitigating Misalignment in RLHF with Hindsight Simulation
Rule-Guided Language Model Alignment for Text Generation Management in Industrial Use Cases
Safe and Sound: Evaluating Language Models for Bias Mitigation and Understanding
Safe Decision Transformer with Learning-based Constraints
Safety-Aware Fine-Tuning of Large Language Models
SCIURus: Shared Circuits for Interpretable Uncertainty Representations in Language Models
Self-Preference Bias in LLM-as-a-Judge
Self-Supervised Bisimulation Action Chunk Representation for Efficient RL
Semantic Membership Inference Attack against Large Language Models
Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
Simulation System Towards Solving Societal-Scale Manipulation
Smoothed Embeddings for Robust Language Models
SolidMark: Evaluating Image Memorization in Generative Models
Steering Without Side Effects: Improving Post-Deployment Control of Language Models
Stronger Universal and Transfer Attacks by Suppressing Refusals
Targeted Unlearning with Single Layer Unlearning Gradient
Testing the Limits of Jailbreaking Defenses with the Purple Problem
The effect of fine-tuning on language model toxicity
The Empirical Impact of Data Sanitization on Language Models
The Impact of Inference Acceleration Strategies on Bias of Large Language Models
The Probe Paradigm: A Theoretical Foundation for Explaining Generative Models
The Structural Safety Generalization Problem
Token Highlighter: Inspecting and Mitigating Jailbreak Prompts for Large Language Models
Towards a Theory of AI Personhood
Towards Inference-time Category-wise Safety Steering for Large Language Models
Towards Resource Efficient and Interpretable Bias Mitigation in Natural Language Generation
Towards Safe and Honest AI Agents with Neural Self-Other Overlap
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
Universal Jailbreak Backdoors in Large Language Model Alignment
Unlearning in- vs. out-of-distribution data in LLMs under gradient-based methods
Variational Diffusion Unlearning: a variational inference framework for unlearning in diffusion models
Waste Not, Want Not; Recycled Gumbel Noise Improves Consistency in Natural Language Generation
Weak-to-Strong Confidence Prediction
What do we learn from inverting CLIP models?
What You See Is What You Get: Entity-Aware Summarization for Reliable Sponsored Search
Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detection
Zer0-Jack: A memory-efficient gradient-based jailbreaking method for black box Multi-modal Large Language Models