ICML 2025PastGenerative models
Data in Generative Models - The Bad, the Ugly, and the Greats
DIG-BUG
- Submission deadline
- May 29, 2025, 12:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (37)
Fetched from OpenReview (v2) on 2026-06-10.
A Data-Centric Safety Framework for Generative Models: Adversarial Fingerprint Detection and Attribution
A Representation Engineering Perspective on the Effectiveness of Multi-Turn Jailbreaks
Backdooring VLMs via Concept-Driven Triggers
Both Text and Images Leaked! A Systematic Analysis of Data Contamination in Multimodal LLMs
Cascading Adversarial Bias from Injection to Distillation in Language Models
COREVQA: A Crowd Observation and Reasoning Entailment Visual Question Answering Benchmark
Data Cartography for Detecting Memorization Hotspots and Guiding Data Interventions in Generative Models
Detective SAM: Adapting SAM to Localize Diffusion-based Forgeries via Embedding Artifacts
Diversity Boosts AI-Generated Text Detection
DP-AdamW: Investigating Decoupled Weight Decay and Bias Correction in Private Deep Learning
FaceSafe: An Inpainting Pipeline for Privacy-Compliant Scalable Image Datasets
Firm Foundations for Membership Inference Attacks Against Large Language Models
Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models
Ghost in the Cloud: Your Geo-Distributed Large Language Models Training is Easily Manipulated
Implementing Adaptations for Vision AutoRegressive Model
Improvement-Guided Iterative DPO for Diffusion Models
In-Context Bias Propagation in LLM-Based Tabular Data Generation
JailbreakLoRA: Your Downloaded LoRA from Sharing Platforms might be Unsafe
Layer-wise Influence Tracing: Data-Centric Mitigation of Memorization in Diffusion Models
Lookahead Bias in Pretrained Language Models
MAD-MAX: Modular And Diverse Malicious Attack MiXtures for Automated LLM Red Teaming
Model-based Large Language Model Customization as Service
Optimal Defenses Against Data Reconstruction Attacks
Optimization and Robustness-Informed Membership Inference Attacks for LLMs
OVERT: A Benchmark for Over-Refusal Evaluation on Text-to-Image Models
Preference Leakage: A Contamination Problem in LLM-as-a-judge
R&B: Breaking the Data Mixing Bottleneck with Just 0.01% Overhead
Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy
RN-F: A Novel Approach for Mitigating Contaminated Data in Large Language Models
SOSBENCH: Benchmarking Safety Alignment on Scientific Knowledge
Spectral Manifold Harmonization for Graph Imbalanced Regression
Training Diffusion Models with Noisy Data via SFBD Flow
TruthLens: Training-Free Data Verification for Deepfake Images via VQA-style Probing
Unlocking Post-hoc Dataset Inference with Synthetic Data
Watermarking Image Autoregressive Models
Weak-to-strong Generalization via Formative Learning from Student Demonstrations & Teacher Evaluation
Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets